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Location: Cairo, Egypt Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Senior Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Senior Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Senior Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Mexico City, Mexico Workplace: hybrid inDrive is a global mobility platform built on fairness: passengers and drivers agree on the price together. We are building a Loyalty Program that rewards passengers for riding with us and gives them real value, not endless promotions. As Partnership Manager, Loyalty, you will own the benefits side of that program globally, across all of inDrive's markets. You will shape the value proposition across three types of benefits: external benefits co-funded by banks, financial groups and consumer brands; internal benefits funded by inDrive; and product benefits built into the app. You will bring partners on board and turn conversations into signed agreements that work in practice, and you will run experiments across all three until we find the mix that passengers actually adopt. You will be the first dedicated hire on this workstream, reporting directly to the Global Director of Loyalty. Disclaimer: CVs in Spanish will NOT be considered. Key Responsibilities Build and prioritize the global partner pipeline, with local depth in your region, choosing partners by fit with the program rather than by the volume they offer. Lead negotiations with Strategic Alliances teams at banks and financial groups, and guide them through their internal approvals (Risk, Legal, Product, Finance). Structure and negotiate term sheets, campaign terms and settlement mechanics together with our Legal and Finance teams. Shape the value proposition for external benefits (partner-funded) and internal benefits (inDrive-funded), and keep both coherent for the passenger. Champion product benefits internally: build the case with Product and other teams so that app features become part of the loyalty offer. Run the experimentation across all benefit types, from hypothesis to test design and readout, until we find the sweet spot of adoption. Work with Product and Fintech teams so every agreement can run on our native product and wallet. Define the partner offer catalog and the criteria for turning down offers that do not give passengers fair value. Track benefit and partner performance (adoption, redemptions, incrementality, return for both sides) and report it to leadership. Represent inDrive in front of partner executives across our markets. Skills, Knowledge & Expertise 6 to 10 years in partnerships, strategic alliances or business development, with at least 3 in loyalty, cashback, fintech, payments, super-apps or marketplaces. A track record negotiating co-funded campaigns or agreements with external funders such as banks, card issuers or large consumer brands. Experience working with Strategic Alliances teams at banks or financial groups and navigating their internal approval chain. Experience structuring deals with Legal and Finance: term sheets, campaign terms, settlements. Hands-on experience designing and running experiments on benefits or offers (A/B tests, pilots) and acting on the results. Comfort with data: you read redemption dashboards and understand incrementality and campaign ROI. Fluent Spanish and English. How you work You influence without authority, moving several internal teams and an external partner at once. You translate between worlds: you can explain our model to a bank and a bank's request to our Legal and Finance teams. You have the judgment to say no to volume that does not serve passengers, and the tact to keep the relationship. You are comfortable building from zero, with no closed playbook. You communicate clearly with executives and work autonomously through long negotiation cycles. You care about fair value for passengers, not only about the size of the funding. Nice to have Experience inside a bank, card issuer or fintech, or an existing network in one or more of inDrive's markets. Knowledge of banking and fintech ecosystems in emerging markets across Latin America, Asia or Africa. Experience with both funding models: partner prefunds the incentive, or the platform advances it and settles later. Background in ride-hailing, delivery or mobility. Having launched a partner program from scratch. Interest in purpose-driven initiatives. Location and team Scope: Global. You will build partnerships and benefits across inDrive's markets in Latin America, Asia, Africa and beyond. Location: Peru, Colombia or Mexico. We will prioritize candidates with a network in Peru or Colombia. Reports to: Global Director of Loyalty. Works with: Product, Fintech, Legal, Finance and the corporate Partnerships team, on a global, English-speaking team.

Location: Lima, Peru Workplace: hybrid inDrive is a global mobility platform built on fairness: passengers and drivers agree on the price together. We are building a Loyalty Program that rewards passengers for riding with us and gives them real value, not endless promotions. As Partnership Manager, Loyalty, you will own the benefits side of that program globally, across all of inDrive's markets. You will shape the value proposition across three types of benefits: external benefits co-funded by banks, financial groups and consumer brands; internal benefits funded by inDrive; and product benefits built into the app. You will bring partners on board and turn conversations into signed agreements that work in practice, and you will run experiments across all three until we find the mix that passengers actually adopt. You will be the first dedicated hire on this workstream, reporting directly to the Global Director of Loyalty. Disclaimer: CVs in Spanish will NOT be considered. Key Responsibilities Build and prioritize the global partner pipeline, with local depth in your region, choosing partners by fit with the program rather than by the volume they offer. Lead negotiations with Strategic Alliances teams at banks and financial groups, and guide them through their internal approvals (Risk, Legal, Product, Finance). Structure and negotiate term sheets, campaign terms and settlement mechanics together with our Legal and Finance teams. Shape the value proposition for external benefits (partner-funded) and internal benefits (inDrive-funded), and keep both coherent for the passenger. Champion product benefits internally: build the case with Product and other teams so that app features become part of the loyalty offer. Run the experimentation across all benefit types, from hypothesis to test design and readout, until we find the sweet spot of adoption. Work with Product and Fintech teams so every agreement can run on our native product and wallet. Define the partner offer catalog and the criteria for turning down offers that do not give passengers fair value. Track benefit and partner performance (adoption, redemptions, incrementality, return for both sides) and report it to leadership. Represent inDrive in front of partner executives across our markets. Skills, Knowledge & Expertise 6 to 10 years in partnerships, strategic alliances or business development, with at least 3 in loyalty, cashback, fintech, payments, super-apps or marketplaces. A track record negotiating co-funded campaigns or agreements with external funders such as banks, card issuers or large consumer brands. Experience working with Strategic Alliances teams at banks or financial groups and navigating their internal approval chain. Experience structuring deals with Legal and Finance: term sheets, campaign terms, settlements. Hands-on experience designing and running experiments on benefits or offers (A/B tests, pilots) and acting on the results. Comfort with data: you read redemption dashboards and understand incrementality and campaign ROI. Fluent Spanish and English. How you work You influence without authority, moving several internal teams and an external partner at once. You translate between worlds: you can explain our model to a bank and a bank's request to our Legal and Finance teams. You have the judgment to say no to volume that does not serve passengers, and the tact to keep the relationship. You are comfortable building from zero, with no closed playbook. You communicate clearly with executives and work autonomously through long negotiation cycles. You care about fair value for passengers, not only about the size of the funding. Nice to have Experience inside a bank, card issuer or fintech, or an existing network in one or more of inDrive's markets. Knowledge of banking and fintech ecosystems in emerging markets across Latin America, Asia or Africa. Experience with both funding models: partner prefunds the incentive, or the platform advances it and settles later. Background in ride-hailing, delivery or mobility. Having launched a partner program from scratch. Interest in purpose-driven initiatives. Location and team Scope: Global. You will build partnerships and benefits across inDrive's markets in Latin America, Asia, Africa and beyond. Location: Peru, Colombia or Mexico. We will prioritize candidates with a network in Peru or Colombia. Reports to: Global Director of Loyalty. Works with: Product, Fintech, Legal, Finance and the corporate Partnerships team, on a global, English-speaking team.

Location: Kuala Lumpur, Malaysia Workplace: hybrid We are looking for a Customer Support Specialist to deliver responsive, professional, and high-quality customer support. This role is key in ensuring customer issues are resolved efficiently while providing an excellent service experience across chat, email, and occasional outbound calls. Key Responsibilities Handle customer inquiries via live chat and email as primary channels, with occasional outbound calls for follow-ups and verification Diagnose, troubleshoot, and resolve customer issues accurately and efficiently Manage returns, exchanges, refunds, and customer complaints in line with company guidelines Maintain accurate and detailed records of customer interactions in the CRM system Provide timely updates to customers on case progress and resolution status Handle complex or unresolved cases by escalating them to the relevant internal teams Ensure proper escalation of issues for investigation and resolution Gather and escalate customer feedback to support continuous improvement Maintain high standards of professionalism, empathy, and service quality in all interactions Support the achievement of CSAT and other performance KPIs Able to work on site Skills, Knowledge and Expertise Minimum 1 year of experience in Customer Service, Technical Support, or Contact Center environment Minimum Diploma in any field Strong typing skills with high accuracy for real-time case handling Ability to multitask and manage 3 to 5 live chat conversations simultaneously Comfortable working in a fast-paced environment with frequent updates and changes Strong communication skills, both written and verbal Good problem-solving and troubleshooting abilities Experience using CRM systems or support tools is an advantage Strong sense of accountability, ownership, and customer focus Reliable with strong attendance and punctuality record Flexibility to be assigned to support different regions on an ad hoc basis Languages: Bahasa( Indonesian), Malay and English are needed. Why join us Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Mexico City, Mexico Workplace: hybrid You’ll be the single point of contact for our fleet partners: running in-person business reviews, solving problems quickly, and building plans that grow their fleets and their earnings on inDrive. Your goal is to turn signed partners into long-term, reliable partnerships — growing their fleet size and utilisation, making sure every incentive pays off in performance, and keeping our partners loyal in a competitive market. This is a hands-on, high-impact role: you’ll work directly with partner owners, our operations and commercial teams, and see the results of your work in the numbers every month. Key Responsibilities Grow your partner portfolio Own the success of our fleet partners in Mexico — helping them activate cars quickly, keep drivers on the road, and grow their business with inDrive Build a joint growth plan with each partner, covering new cars, utilisation goals and expansion into new cities Run regular in-person business reviews, using live performance data to spot opportunities and fix problems early Manage the commercial relationship Manage each partner’s incentive programme, making sure rewards follow real performance Handle contract renewals and negotiate terms when a partnership needs to change Work with our commercial team on non-standard deals and keep all agreements up to date Keep operations running smoothly Partner with our driver operations team to get new drivers onboarded and active fast Help partners get the most out of our fleet management tools, so they can run their business more independently Be the go-to person when issues come up Bring the market to us Keep a close eye on competitors and what they offer Share what you learn from the field to help shape our partnership strategy Skills, Knowledge & Expertise Required 3+ years in key account management in B2B, mobility, logistics or marketplaces Track record of growing large accounts in person, with joint business plans and reviews Strong commercial and analytical skills: comfortable with performance data, incentive economics and dashboards Fluent in the local language and good in English Preferred Experience with fleet operators, taxi parks, car rental or automotive dealers Existing network among local fleet owners Exposure to ride-hailing or other two-sided marketplaces Job Benefits Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Bogotá, Colombia Workplace: hybrid inDrive is a global mobility platform built on fairness: passengers and drivers agree on the price together. We are building a Loyalty Program that rewards passengers for riding with us and gives them real value, not endless promotions. As Partnership Manager, Loyalty, you will own the benefits side of that program globally, across all of inDrive's markets. You will shape the value proposition across three types of benefits: external benefits co-funded by banks, financial groups and consumer brands; internal benefits funded by inDrive; and product benefits built into the app. You will bring partners on board and turn conversations into signed agreements that work in practice, and you will run experiments across all three until we find the mix that passengers actually adopt. You will be the first dedicated hire on this workstream, reporting directly to the Global Director of Loyalty. Disclaimer: CVs in Spanish will NOT be considered. Key Responsibilities Build and prioritize the global partner pipeline, with local depth in your region, choosing partners by fit with the program rather than by the volume they offer. Lead negotiations with Strategic Alliances teams at banks and financial groups, and guide them through their internal approvals (Risk, Legal, Product, Finance). Structure and negotiate term sheets, campaign terms and settlement mechanics together with our Legal and Finance teams. Shape the value proposition for external benefits (partner-funded) and internal benefits (inDrive-funded), and keep both coherent for the passenger. Champion product benefits internally: build the case with Product and other teams so that app features become part of the loyalty offer. Run the experimentation across all benefit types, from hypothesis to test design and readout, until we find the sweet spot of adoption. Work with Product and Fintech teams so every agreement can run on our native product and wallet. Define the partner offer catalog and the criteria for turning down offers that do not give passengers fair value. Track benefit and partner performance (adoption, redemptions, incrementality, return for both sides) and report it to leadership. Represent inDrive in front of partner executives across our markets. Skills, Knowledge & Expertise 6 to 10 years in partnerships, strategic alliances or business development, with at least 3 in loyalty, cashback, fintech, payments, super-apps or marketplaces. A track record negotiating co-funded campaigns or agreements with external funders such as banks, card issuers or large consumer brands. Experience working with Strategic Alliances teams at banks or financial groups and navigating their internal approval chain. Experience structuring deals with Legal and Finance: term sheets, campaign terms, settlements. Hands-on experience designing and running experiments on benefits or offers (A/B tests, pilots) and acting on the results. Comfort with data: you read redemption dashboards and understand incrementality and campaign ROI. Fluent Spanish and English. How you work You influence without authority, moving several internal teams and an external partner at once. You translate between worlds: you can explain our model to a bank and a bank's request to our Legal and Finance teams. You have the judgment to say no to volume that does not serve passengers, and the tact to keep the relationship. You are comfortable building from zero, with no closed playbook. You communicate clearly with executives and work autonomously through long negotiation cycles. You care about fair value for passengers, not only about the size of the funding. Nice to have Experience inside a bank, card issuer or fintech, or an existing network in one or more of inDrive's markets. Knowledge of banking and fintech ecosystems in emerging markets across Latin America, Asia or Africa. Experience with both funding models: partner prefunds the incentive, or the platform advances it and settles later. Background in ride-hailing, delivery or mobility. Having launched a partner program from scratch. Interest in purpose-driven initiatives. Location and team Scope: Global. You will build partnerships and benefits across inDrive's markets in Latin America, Asia, Africa and beyond. Location: Peru, Colombia or Mexico. We will prioritize candidates with a network in Peru or Colombia. Reports to: Global Director of Loyalty. Works with: Product, Fintech, Legal, Finance and the corporate Partnerships team, on a global, English-speaking team.

Location: Sao Paulo, Brazil (Sao Paulo) Workplace: hybrid As a Driver Marketing Specialist, you will own driver marketing in Brazil, from insights and communication strategy to campaign launches in the market. You'll work closely with the Driver Operations, Brand, Analytics, and regional marketing teams, and you'll have real influence on the growth of one of our key markets. Key Responsibilities Turn BHT and competitor insights into clear recommendations for driver positioning, messaging, and campaigns; create and execute communication plans, and manage the driver marketing budget. Measure the impact of marketing activities through pre/post studies and ad testing, and connect brand KPIs with business results such as sign-ups and retention. Align with the Driver Ops team on acquisition campaigns, referral programs and lifecycle communications, so that all driver touchpoints stay consistent with the brand strategy. Lead 360 campaign launches and marketing activities in the market. Skills, Knowledge & Expertise 2+ years of experience in marketing, ideally in ride-hailing, delivery, marketplaces or other two-sided platforms. A solid understanding of brand health tracking. A deep understanding of the Brazilian market, plus strong cross-functional skills to align several teams around one brand vision. Strong planning skills, the ability to adapt quickly to changing market conditions, and confidence in making decisions. English B2+ Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Geo Search runs the search that tens of millions of customers use to say where they are going, across many countries where the commercial maps everyone else leans on are often wrong, incomplete, or simply missing. We are building our own search and recommendation stack, which means we own the data, the ranking, and the measurement. The team is cross-functional, spanning backend, machine learning, mobile, and QA, and works with a product manager focused on relevance and with geo analysts. It owns place search and autocomplete, geocoding, ranking and personalization, location detection and pickup selection, and its own search screens on Android and iOS. It is measured on order conversion, search conversion, and mean reciprocal rank We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context. This is a modeling role with production responsibility, and it is close to a founding one. You will define how relevance is measured here, build the training data from scratch, and own the models that follow. The interesting constraint is that suggestions must return within tens of milliseconds of each keystroke, in cities where map data is thin and people type in mixed scripts, so model choice is an evidence-based trade-off you will own rather than a preference: gradient-boosted ranking on behavioral data today, transformers and large language models where they earn their place in query understanding and cross-script matching, and neural reranking if the failure analysis justifies it. Ground truth comes from what drivers, couriers and customers actually do, and from completed rides, so a large part of the craft is turning messy behavioral logs into labels you can trust. You will measure your impact through offline evaluation and online A/B tests, and changes reach millions of customers in weeks. Key Responsibilities Own ranking, relevance and recommendation for geo search end to end, from training data through to models serving in production Build the label pipeline that turns search sessions and completed rides into trustworthy training data, including correction for position bias and other presentation effects Train and own the models that order results, and the confidence model that decides per query whether we serve our own answer or fall back to an external provider Build query understanding for our markets, including cross-script matching, using large language models to label offline and distilling into models fast enough for the keystroke path Own evaluation end to end: the offline replay harness that scores recorded sessions against real rides, the error analysis that turns failures into work for the right team, and the online experiments that prove impact Keep models healthy after launch as data and cities shift Skills, Knowledge and Expertise Minimum qualifications 5 or more years building models that shipped and improved a production metric Direct experience with ranking, search relevance, or recommendation systems, including how they are evaluated Expert Python and SQL, fluency with gradient boosting, and working knowledge of transformers Experience taking a model to production and owning it afterwards The ability to work across teams, since search quality work generates data and engineering tasks that others own Preferred qualifications Depth in geocoding, autocomplete, or place search Learning to rank in practice: pairwise and listwise objectives, MRR, NDCG, Hit@k, and their failure modes Relevance tuning on OpenSearch or Elasticsearch, including analyzers Multilingual or cross-script search, for example Arabic and Arabizi or Urdu and Roman Urdu Distilling language models under a latency budget, and experience in mapping or geospatial products in developing markets Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid Geo Search runs the search that tens of millions of customers use to say where they are going, across many countries where the commercial maps everyone else leans on are often wrong, incomplete, or simply missing. We are building our own search and recommendation stack, which means we own the data, the ranking, and the measurement. The team is cross-functional, spanning backend, machine learning, mobile, and QA, and works with a product manager focused on relevance and with geo analysts. It owns place search and autocomplete, geocoding, ranking and personalization, location detection and pickup selection, and its own search screens on Android and iOS. It is measured on order conversion, search conversion, and mean reciprocal rank We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context. This is a modeling role with production responsibility, and it is close to a founding one. You will define how relevance is measured here, build the training data from scratch, and own the models that follow. The interesting constraint is that suggestions must return within tens of milliseconds of each keystroke, in cities where map data is thin and people type in mixed scripts, so model choice is an evidence-based trade-off you will own rather than a preference: gradient-boosted ranking on behavioral data today, transformers and large language models where they earn their place in query understanding and cross-script matching, and neural reranking if the failure analysis justifies it. Ground truth comes from what drivers, couriers and customers actually do, and from completed rides, so a large part of the craft is turning messy behavioral logs into labels you can trust. You will measure your impact through offline evaluation and online A/B tests, and changes reach millions of customers in weeks. Key Responsibilities Own ranking, relevance and recommendation for geo search end to end, from training data through to models serving in production Build the label pipeline that turns search sessions and completed rides into trustworthy training data, including correction for position bias and other presentation effects Train and own the models that order results, and the confidence model that decides per query whether we serve our own answer or fall back to an external provider Build query understanding for our markets, including cross-script matching, using large language models to label offline and distilling into models fast enough for the keystroke path Own evaluation end to end: the offline replay harness that scores recorded sessions against real rides, the error analysis that turns failures into work for the right team, and the online experiments that prove impact Keep models healthy after launch as data and cities shift Skills, Knowledge and Expertise Minimum qualifications 5 or more years building models that shipped and improved a production metric Direct experience with ranking, search relevance, or recommendation systems, including how they are evaluated Expert Python and SQL, fluency with gradient boosting, and working knowledge of transformers Experience taking a model to production and owning it afterwards The ability to work across teams, since search quality work generates data and engineering tasks that others own Preferred qualifications Depth in geocoding, autocomplete, or place search Learning to rank in practice: pairwise and listwise objectives, MRR, NDCG, Hit@k, and their failure modes Relevance tuning on OpenSearch or Elasticsearch, including analyzers Multilingual or cross-script search, for example Arabic and Arabizi or Urdu and Roman Urdu Distilling language models under a latency budget, and experience in mapping or geospatial products in developing markets Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary from 70 700 EUR gross Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid We are looking for a Strategy & Operations Manager to act as an independent execution and problem-solving partner to the business leadership team. This is not a traditional PMO role. The mandate is broader: create transparency, challenge performance, solve cross-functional problems, and make sure our most important initiatives actually get delivered. You will work horizontally across Product, Operations, Commercial, Finance, Legal, and other functions, with visibility across the full portfolio of strategic initiatives. Your job is simple to describe but difficult to execute: know what matters, know what is happening, identify what is not working, and drive it to resolution. Key Responsibilities 1. Own strategic execution Maintain an end-to-end view of the business's most critical initiatives and their performance. Translate strategic priorities into clear projects, milestones, owners, KPIs, and deadlines. Drive high-priority projects directly when dedicated ownership is missing or additional execution power is required. Ensure commitments turn into measurable outcomes-not just meetings, updates, and presentations. Step into stalled or ambiguous initiatives and drive them back to execution. 2. Act as an independent performance partner Build a fact-based view of whether projects, teams, and initiatives are delivering against expectations. Challenge assumptions, timelines, priorities, and reported progress when necessary. Identify gaps between reported status and actual business impact. Diagnose underperformance and distinguish between strategy, execution, ownership, resource, and capability problems. Escalate material risks early and ensure corrective actions are defined and executed. 3. Solve cross-functional problems Step into the "messy middle" between functions where ownership is unclear and execution gets stuck. Structure ambiguous problems quickly and turn them into actionable decisions. Align Product, Operations, Finance, Legal, Commercial, and other stakeholders around a single execution path. Identify blockers, resolve dependencies, and drive decisions with pace. Act as a neutral partner focused on the overall business outcome rather than the interests of an individual function. 4. Build execution discipline Establish a lightweight but rigorous operating rhythm for strategic initiatives. Create a single source of truth for priorities, status, decisions, risks, and dependencies. Ensure every critical initiative has clear ownership, measurable outcomes, and transparent progress. Run project and portfolio reviews focused on decisions and actions rather than status reporting. Continuously improve how the organisation manages projects and executes strategic priorities. 5. Support strategic decision-making Turn complex operational and performance data into clear management insights. Build business cases and conduct quantitative and qualitative analysis for major strategic decisions. Evaluate new opportunities, growth bets, and operating-model improvements. Prepare concise, decision-oriented materials for senior leadership. Connect strategy with execution: understand not only what we should do, but whether and how the organisation can actually deliver it. What success looks like Success in this role is not measured by the number of projects tracked or meetings facilitated. It is measured by: Transparency - leadership always knows the real status of critical priorities. Accountability - every important outcome has an owner, deadline, and measurable result. Speed - blockers and unresolved decisions do not remain unresolved for weeks. Execution quality - strategic initiatives move from discussion to implementation. Business impact - the portfolio delivers measurable improvements in growth, efficiency, quality, or scalability. Qualifications You should be: Extremely structured and comfortable bringing order to ambiguity. Strong in project and program management, with the ability to lead multiple critical initiatives simultaneously. Highly analytical and able to independently challenge numbers, assumptions, and conclusions. Comfortable working directly with senior leaders and holding stakeholders accountable. Able to influence without formal authority. Pragmatic and execution-oriented-you naturally move from discussion to decision to action. Comfortable entering unfamiliar areas, learning quickly, and solving problems independently. Strong at communicating complex topics simply and concisely. Naturally curious and persistent: when something does not make sense, you keep digging until it does. The ideal candidate does not simply track the business. They help the business execute better. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary from 75 600 EUR gross Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Delivery Hub is one of inDrive’s business units responsible for building and scaling the delivery product, which is rapidly expanding into new markets and adopting an AI-first approach to engineering processes. We are looking for a Tech Lead who will combine hands-on engineering with leadership responsibilities: owning team delivery and execution, defining technical direction and ensuring solution quality, as well as supporting engineers’ growth through feedback, mentoring, and regular 1:1s under the guidance of an Engineering Manager. Key Responsibilities Translate business needs into a technical strategy with measurable outcomes. Ensure alignment with the global company strategy. Identify and propose architectural and technical improvements across the product and platform, using data and trade-off analysis. Advocate, present, and defend technical solutions at the organizational level in collaboration with various stakeholders (Product, Data, Security, SRE, etc.). Participate in reviewing product & technical strategies as a subject-matter expert. Lead the process of technical research and implementation to create or improve services and systems. Write clean, effective, and maintainable code based on company standards. Participate in improving company-wide code and review standards. Take ownership of and improve the Android development lifecycle. Help engineers grow and increase their productivity. Create effective processes for knowledge sharing and collaborative work. Increase the re-use of best practices across teams. Lead task decomposition; mentor engineers and contribute to engineering guidelines. Skills, Knowledge and Expertise 6+ years of commercial Android development; expert in Kotlin and modern Android APIs. Hands-on experience with Retrofit/OkHttp, Coroutines/Flow (plus RxJava for legacy), Jetpack (Compose, WorkManager), Google Maps, FCM, and Gradle. Proven experience with CI/CD (GitHub Actions/GitLab CI), feature flags, and large-scale A/B experimentation. Strong grasp of offline storage, concurrency, performance tuning, and network debugging. Practical expertise in Clean Architecture and mainstream patterns (MVI/MVVM/MVP) applied in production. Deep understanding of client-server interaction and how to make it efficient. Knowledge of specific features and limitations for various use cases. Proven record of mentoring and technical leadership, shaping processes, and raising engineering quality across teams. Strong grasp of backend-service principles, API design, networking, concurrency, and performance optimization. Experience setting up telemetry, dashboards, and automated alerts for production systems; risk assessment and mitigation. Exceptional communication, strategic thinking, and influence; able to drive alignment across multiple teams. AI-first mindset and readiness to adopt AI tools in engineering processes. Real backend development experience is a strong plus. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid The AI Solution Delivery team is expanding its capabilities in NLP to build production-grade AI products. We are looking for a Senior Data Scientist to architect, build and deploy complex models for automating customer support operations. You will be responsible for selecting the right technical approaches and ensuring the scalability of our solutions. A proven track record in applying advanced NLP techniques to real-world problems is required. Key Responsibilities Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance Translate complex business goals into well defined data science problems and quantifiable metrics Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance Support the development and growth of other team members through mentorship and participation in onboarding programs Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact Communicate complex technical concepts and findings clearly and concisely to both technical and non technical stakeholders Skills, Knowledge and Expertise 5 years of professional experience in a data science or machine learning role with deep focus on NLP. Previous software engineering experience is preferrable. An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus Expert level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit learn). Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields. Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment. Proven experience with event systems, deployment environments, and maintaining production services. Familiarity with technologies for streaming, batch, and async data processing. Strong understanding of software system design principles and the ability to contribute to architectural discussions. Experience in experimental design to validate hypotheses and measure the effectiveness of solutions. A solid grasp of security, risk, and control concepts in a production environment. Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Abu Dhabi, United Arab Emirates Workplace: hybrid Autonomous vehicles are coming to the markets in which inDrive serves, but the AV industry has a blind spot: it has almost no data from the cities where we operate. inDrive runs one of the world's largest ride-hailing fleets, concentrated in exactly the emerging markets global AV players have yet to reach. We are building the team that turns that fleet into an AV grade data platform: large scale multi sensor collection from real vehicles on real trips, evaluation of driving models against human drivers, automated and human in the loop causal annotation, and camera first 3D scene reconstruction for simulation. We are hiring the founding leader of this workstream. This is a rare true zero to one: you will hire the team, stand up the vehicles and the data platform, set the technical bar, and own delivery end to end. Key Responsibilities Own the AV data workstream end to end. Roadmap, execution, quality, and outcomes, from vehicle data capture through processing, annotation, and delivery of AV-grade datasets Build the team from zero. Hire and lead a multi disciplinary team covering large scale data engineering, search and serving, ML engineering across divergence detection, edge inference, and VLM based auto labeling, 3D reconstruction research, and data annotation operations. Own the hiring bar and the team's growth Management : Manage ML engineers' charter across the cluster Set technical direction across disciplines. Provide design authority for the full pipeline, including onboard capture, cloud ingestion and processing at fleet scale, semantic and causal labeling, and neural scene reconstruction, and make the key technical decisions on evidence Partner with leaders across the organization. Work closely with the leaders of data platform, ML ops, geo and mapping, and inDrive's wider autonomous vehicle initiatives to align roadmaps, share infrastructure, and unblock delivery Own external partnerships. Drive the technical relationships this work depends on, including the NVIDIA AV ecosystem and prospective AV partners consuming our data Balance research and delivery. Several of the core questions here are open research. You frame milestones as decision gates, redirect work based on evidence, and keep the team shipping measurable results on a schedule Skills, Knowledge and Expertise 10+ years of engineering experience in applied ML, autonomous systems, or large-scale data and ML platforms, including 3+ years in the autonomous vehicle industry or closely adjacent autonomy domains (AV data, simulation, or evaluation platforms, ADAS, robotics perception, HD mapping), and 4+ years managing engineering teams, with a track record of building teams from scratch and delivering from zero to one Strong command of the modern AV and foundation model landscape: vision-language models, multi-modal perception, 3D reconstruction and neural rendering, and the NVIDIA AV ecosystem. Deep enough to set direction, review designs, and make evidence-based technical calls Genuine engineering leadership range: you have successfully led data engineering, platform, or infrastructure delivery, not only ML research, and can evaluate and unblock work across those disciplines Proven ability to take large-scale ML systems from conception to production: data pipelines, training and evaluation infrastructure, and models running under real-world constraints Strong external presence: experience owning technical partnerships, vendor and licensing relationships, or customer-facing technical engagements at a senior level Deep fluency in the modern ML stack (PyTorch or equivalent, large-scale training and inference, Python and Linux) and in cloud data platforms at multi-terabyte scale Bachelor's degree in Computer Science, Engineering, or a related field Nice to have: AV industry experience specifically in offline evaluation, data mining, annotation platforms, or simulation, as distinct from on-vehicle stack development Advanced degree (MS or PhD) in ML, robotics, or computer vision Experience operating in emerging markets, and comfort building where the playbook does not exist yet Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects Work alongside people who take initiative, speak openly, and challenge themselves to grow Improve your language skills through co-financed courses and internal speaking clubs Final benefits may vary depending on the location.

Location: Lima, Peru Workplace: hybrid We are looking for a data-driven Senior Product Marketing Manager to own the strategy, execution, and continuous optimization of our customer lifecycle and product engagement initiatives. Key Responsibilities Campaign Preparation and Execution: Independently create, schedule, and execute marketing campaigns (email, push notifications, WhatsApp, in-app messages, banners) across multiple customer segments. Optimize campaigns for delivery across time zones, devices, and customer preferences. Ensure compliance with legal standards such as GDPR and other regional requirements. Audience Segmentation: Design and implement custom segmentation strategies based on multidimensional criteria such as behavior, demographics, orders and ride history, and engagement levels. Maintain dynamic customer segments that update automatically as data changes. Trigger Campaign Configuration: Build and manage multi-step automated workflows, such as re-engagement, loyalty program adoption, or upselling campaigns, with minimal supervision. Test and troubleshoot triggers to ensure proper execution and alignment with the customer lifecycle. Testing and Optimization: Plan, execute, and document A/B and multivariate tests for key campaign elements, including design, timing, and messaging. Use insights from testing to implement data-driven improvements across campaigns. Perform regular performance reviews to refine optimization strategies. Reporting and Analysis: Generate detailed reports on campaign performance, interpreting metrics like open rates, CTRs, conversions, and ROI. Present data insights to stakeholders and provide actionable recommendations to improve rider and driver engagement. Collaboration and Mentoring: Collaborate with cross-functional teams (content, design, analytics) to deliver campaigns. Provide guidance and support to junior CRM specialists, including peer reviews and knowledge sharing. Skills, Knowledge & Expertise CRM Platform Proficiency: Independently execute at least five end-to-end campaigns quarterly using advanced CRM platform features (e.g., Bloomreach, Salesforce Marketing Cloud, HubSpot). Build at least three advanced automations quarterly, such as multi-step workflows with branching logic (e.g., loyalty or churn prevention campaigns). Complete at least two courses with intermediate certification for Bloomreach or demonstrate equivalent expertise. Data Analysis and Reporting: Create detailed reports with data visualizations for at least five campaigns quarterly, incorporating metrics like open rates, conversion rates, and ARPPU. Work with datasets using tools like Excel or Google Sheets with advanced functions (e.g., INDEX/MATCH, QUERY). Present campaign insights to stakeholders in three formal presentations with actionable recommendations. Digital Marketing Expertise: Apply intermediate-level knowledge of digital marketing strategies, including personalization, retargeting, and customer journey mapping. Assist in the strategic planning of at least two multi-channel campaigns integrating email, WhatsApp, in-app, banners, and push notifications. Advanced Data Handling: Segment audiences dynamically based on real-time data, using at least three different criteria simultaneously. Ensure data compliance by implementing processes that align with GDPR/CCPA requirements for all campaigns. English Proficiency: Write comprehensive campaign briefs and reports in English, ensuring accuracy and clarity. Lead or co-lead three cross-functional meetings in English, presenting updates or insights confidently. Advanced Testing and Optimization: Conduct and analyze A/B tests for at least five campaigns quarterly, including testing subject lines, offers, layouts, and timing. Implement changes based on test results, achieving measurable improvements in key KPIs (e.g., a 5 statistically significant lift in conversion). Communication Deliverability: Monitor and resolve deliverability issues for campaigns. Use tools like Postmaster Tools or delivery reports to troubleshoot spam issues and optimize sender reputation. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid You will lead analytics for the Services cluster — the set of domains that protect trust, safety, and quality across every interaction on our platform. This is where the integrity of the marketplace is safeguarded and where millions of passengers and drivers experience inDrive as a safe and reliable place to be. Your teams will span five closely connected areas: Watchdocs (driver document verification and work with the compliance base), Trust & Safety (everything related to trust and safety in rides — incidents and safety features), Customer Support (both the product tooling for handling user requests and the automation of that work, plus WFM analytics of support agents' performance), Customer Experience (Voice-of-the-Customer feedback and connecting satisfaction metrics such as CSAT/DSAT to business metrics), and Antifraud (protecting rides, transactions, ratings, and more from abuse across inDrive). You will build and manage a team that partners closely with product, operations, support, and compliance to turn a large volume of behavioral, operational, and feedback signals into decisions that reduce risk and improve experience at the same time. From detecting and quantifying fraud across rides and transactions, to measuring the real business impact of safety features and support automation, to linking customer-feedback metrics (CSAT/DSAT) with core business outcomes — your work will define how the company balances protection, cost, and user satisfaction. In this role, you will act as a strategic partner to product and business leaders, as well as to Trust & Safety and Compliance stakeholders — shaping the analytics agenda for the Services cluster, defending its strategy in front of senior leadership, and building scalable processes, metrics, and standards that make trust and safety measurable across the whole platform. Key Responsibilities Own the analytics strategy and roadmap for the Services cluster (Watchdocs, Trust & Safety, Customer Support, CX, Antifraud), align it with company-level priorities, and defend it in front of senior leadership Build, grow, and develop a team of 11+ (analysts) — hiring, mentoring, and setting quality standards across the cluster Lead Antifraud analytics : detect and quantify fraudulent behavior across rides, transactions, and ratings; evaluate the effectiveness of anti-fraud rules and models and their trade-off with false positives Drive Trust & Safety analytics : measure incident rates, evaluate the impact of safety features, and help prioritize initiatives that reduce risk for passengers and drivers Oversee Customer Support analytics : assess support tooling and automation effectiveness, contact-rate drivers, resolution quality, and WFM analytics for agent capacity and performance Lead CX analytics : connect Voice-of-the-Customer metrics (CSAT/DSAT) to business outcomes such as retention and revenue, and turn feedback into prioritized product and operational actions Guide Watchdocs analytics : the document-verification funnel, compliance coverage, and the balance between compliance rigor and a smooth driver onboarding experience Define and standardize metrics, definitions, and monitoring across the cluster; ensure data quality in partnership with DWH, DS, and Engineering Establish best practices in experimentation (A/B testing), causal inference, forecasting, and effect measurement across the team Partner cross-functionally at the company level (Product & Tech & Business, DWH, DS, Engineering) and act as a trusted advisor to Head / Director / C-suite stakeholders Skills, Knowledge and Expertise 6+ years of experience in data or product analytics, preferably in tech, ride-hailing, marketplace, or platform businesses 2+ years of people management, leading teams of 10+ people, including other managers or team leads Strong expertise in SQL and Python (or R), with a solid foundation in statistics and experimentation (A/B testing, causal inference) Proven ability to translate large volumes of behavioral, operational, and feedback data into decisions that balance risk, cost, and user experience Experience partnering with senior stakeholders (Head / Director / C-suite) and forming and defending strategy at the company level Proficiency in BI tools (Tableau, Looker, Redash, or similar) Strong communication skills and the ability to present complex findings clearly to both technical and non-technical audiences English proficiency at B2 or higher for international collaboration Nice to Have Hands-on experience in one of the Services domains — Trust & Safety, Antifraud, Customer Support / WFM, CX / Voice-of-the-Customer, or compliance Experience with fraud / risk modeling, anomaly detection, or safety analytics Familiarity with text / sentiment analysis for customer-feedback data Experience scaling analytics across multiple countries and verticals Why join us Help us challenge injustice by creating fair choices for millions of people across 48 countries Develop your professional skills with access to mentoring, career consulting, and learning programs Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects Work alongside people who take initiative, speak openly, and challenge themselves to grow Improve your language skills through co-financed courses and internal speaking clubs Annual salary from EUR 90 700 gross Final benefits may vary depending on the location.

Location: Tbilisi, Georgia Workplace: hybrid Geo Search runs the search that tens of millions of customers use to say where they are going, across many countries where the commercial maps everyone else leans on are often wrong, incomplete, or simply missing. We are building our own search and recommendation stack, which means we own the data, the ranking, and the measurement. The team is cross-functional, spanning backend, machine learning, mobile, and QA, and works with a product manager focused on relevance and with geo analysts. It owns place search and autocomplete, geocoding, ranking and personalization, location detection and pickup selection, and its own search screens on Android and iOS. It is measured on order conversion, search conversion, and mean reciprocal rank We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context. This is a modeling role with production responsibility, and it is close to a founding one. You will define how relevance is measured here, build the training data from scratch, and own the models that follow. The interesting constraint is that suggestions must return within tens of milliseconds of each keystroke, in cities where map data is thin and people type in mixed scripts, so model choice is an evidence-based trade-off you will own rather than a preference: gradient-boosted ranking on behavioral data today, transformers and large language models where they earn their place in query understanding and cross-script matching, and neural reranking if the failure analysis justifies it. Ground truth comes from what drivers, couriers and customers actually do, and from completed rides, so a large part of the craft is turning messy behavioral logs into labels you can trust. You will measure your impact through offline evaluation and online A/B tests, and changes reach millions of customers in weeks. Key Responsibilities Own ranking, relevance and recommendation for geo search end to end, from training data through to models serving in production Build the label pipeline that turns search sessions and completed rides into trustworthy training data, including correction for position bias and other presentation effects Train and own the models that order results, and the confidence model that decides per query whether we serve our own answer or fall back to an external provider Build query understanding for our markets, including cross-script matching, using large language models to label offline and distilling into models fast enough for the keystroke path Own evaluation end to end: the offline replay harness that scores recorded sessions against real rides, the error analysis that turns failures into work for the right team, and the online experiments that prove impact Keep models healthy after launch as data and cities shift Skills, Knowledge and Expertise Minimum qualifications 5 or more years building models that shipped and improved a production metric Direct experience with ranking, search relevance, or recommendation systems, including how they are evaluated Expert Python and SQL, fluency with gradient boosting, and working knowledge of transformers Experience taking a model to production and owning it afterwards The ability to work across teams, since search quality work generates data and engineering tasks that others own Preferred qualifications Depth in geocoding, autocomplete, or place search Learning to rank in practice: pairwise and listwise objectives, MRR, NDCG, Hit@k, and their failure modes Relevance tuning on OpenSearch or Elasticsearch, including analyzers Multilingual or cross-script search, for example Arabic and Arabizi or Urdu and Roman Urdu Distilling language models under a latency budget, and experience in mapping or geospatial products in developing markets Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.