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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: 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: Jakarta, Indonesia Workplace: hybrid inDrive's Forecasting product turns large-scale marketplace data into daily and monthly forecasts of the company's core supply, demand and financial metrics. These forecasts are the backbone of target setting, financial planning and scenario analysis for business teams and leadership. We are looking for a Senior Analyst to own this product: the quality and credibility of the numbers, the planning processes they feed, and the story behind every deviation. You will take over a working production solution (Python, BigQuery) and keep it reliably serving the business — but the core of the role is not modeling for its own sake. It is understanding how the business works: how pricing, incentives, marketing and market events move metrics, how those metrics connect to each other, and what decision-makers need from a forecast to plan with confidence. Key Responsibilities Business & planning Own the forecast as a decision-making product: track plan vs actual, decompose variances into business drivers (seasonality, pricing, incentives, marketing, external events), and explain in business terms why the numbers changed Support company planning cycles: provide forecast baselines for target setting and budgeting, and align assumptions with finance and business stakeholders Build and run scenario ("what-if") analysis for planned interventions: pricing changes, incentive and marketing spend, product launches, market expansion Maintain the dependency logic connecting supply, demand and financial metrics, so that forecasts stay mutually consistent and aggregate correctly across markets Translate ambiguous business questions into measurable forecasting problems; communicate assumptions, uncertainty and limitations clearly to both business and technical audiences Forecast production Run and monitor recurring daily and monthly forecasts: data completeness, sanity checks, run-over-run drift Investigate anomalies end to end — from inputs and business transformations to forecast outputs — getting to the business reason, not just a technical fix Improve models pragmatically: baselines, honest validation, and model choices driven by measurable planning value rather than sophistication. Keep the solution maintainable: readable Python, documentation, versioned changes Skills, Knowledge and Expertise 4+ years in analytics, forecasting or planning roles — for example marketplace or product analytics, demand planning, or decision science Strong understanding of how a business is planned: plan/fact cycles, target setting, driver-based models, unit economics. You see business metrics as a connected system, not as isolated time series Practical command of time-series forecasting — seasonality, holidays, external regressors, structural breaks, missing data — enough to own and improve production models Confident Python (pandas ecosystem): able to maintain and extend an existing production codebase Advanced SQL and experience with large datasets in a cloud data warehouse Rigorous validation habits: appropriate baselines, no data leakage, error metrics tied to business impact Ownership mindset: comfortable investigating issues across data, model, and integration boundaries Professional working proficiency in English and the ability to defend a number in front of senior stakeholders Nice to have: Background in mobility, marketplaces or other supply-and-demand systems Experience supporting financial planning, S&OP or budgeting processes Econometrics and causal inference; marketing-response models (adstock, saturation, investment payback) Hierarchical forecasting across multiple markets Experience owning or supporting production batch pipelines; BigQuery, Git-based workflows, CI/CD Technology environment Python (pandas, NumPy, scikit-learn, Prophet), BigQuery, Databricks, Git and GitHub Actions. This is an analyst role in an engineering-friendly environment: you should be at home in this stack, but deep ML engineering is not the core of the job. 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 inDrive's Forecasting product turns large-scale marketplace data into daily and monthly forecasts of the company's core supply, demand and financial metrics. These forecasts are the backbone of target setting, financial planning and scenario analysis for business teams and leadership. We are looking for a Senior Analyst to own this product: the quality and credibility of the numbers, the planning processes they feed, and the story behind every deviation. You will take over a working production solution (Python, BigQuery) and keep it reliably serving the business — but the core of the role is not modeling for its own sake. It is understanding how the business works: how pricing, incentives, marketing and market events move metrics, how those metrics connect to each other, and what decision-makers need from a forecast to plan with confidence. Key Responsibilities Business & planning Own the forecast as a decision-making product: track plan vs actual, decompose variances into business drivers (seasonality, pricing, incentives, marketing, external events), and explain in business terms why the numbers changed Support company planning cycles: provide forecast baselines for target setting and budgeting, and align assumptions with finance and business stakeholders Build and run scenario ("what-if") analysis for planned interventions: pricing changes, incentive and marketing spend, product launches, market expansion Maintain the dependency logic connecting supply, demand and financial metrics, so that forecasts stay mutually consistent and aggregate correctly across markets Translate ambiguous business questions into measurable forecasting problems; communicate assumptions, uncertainty and limitations clearly to both business and technical audiences Forecast production Run and monitor recurring daily and monthly forecasts: data completeness, sanity checks, run-over-run drift Investigate anomalies end to end — from inputs and business transformations to forecast outputs — getting to the business reason, not just a technical fix Improve models pragmatically: baselines, honest validation, and model choices driven by measurable planning value rather than sophistication. Keep the solution maintainable: readable Python, documentation, versioned changes Skills, Knowledge and Expertise 4+ years in analytics, forecasting or planning roles — for example marketplace or product analytics, demand planning, or decision science Strong understanding of how a business is planned: plan/fact cycles, target setting, driver-based models, unit economics. You see business metrics as a connected system, not as isolated time series Practical command of time-series forecasting — seasonality, holidays, external regressors, structural breaks, missing data — enough to own and improve production models Confident Python (pandas ecosystem): able to maintain and extend an existing production codebase Advanced SQL and experience with large datasets in a cloud data warehouse Rigorous validation habits: appropriate baselines, no data leakage, error metrics tied to business impact Ownership mindset: comfortable investigating issues across data, model, and integration boundaries Professional working proficiency in English and the ability to defend a number in front of senior stakeholders Nice to have: Background in mobility, marketplaces or other supply-and-demand systems Experience supporting financial planning, S&OP or budgeting processes Econometrics and causal inference; marketing-response models (adstock, saturation, investment payback) Hierarchical forecasting across multiple markets Experience owning or supporting production batch pipelines; BigQuery, Git-based workflows, CI/CD Technology environment Python (pandas, NumPy, scikit-learn, Prophet), BigQuery, Databricks, Git and GitHub Actions. This is an analyst role in an engineering-friendly environment: you should be at home in this stack, but deep ML engineering is not the core of the job. 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 EUR 70 700 gross Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Machine Learning Engineer , who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential. Key Responsibilities Develop, deploy, and maintain machine learning models and systems Conduct in-depth data analysis, preparation, and processing Contribute to the design of ML systems, focusing on data-related aspects like annotation and processing Follow established security guidelines and identify potential risks Collaborate with peers to review and ensure designs are effective, flexible, and reusable Solve issues and provide feedback for engineering design and delivery processes Ensure that features are deployed according to requirements and operate without unintended side effects Create and maintain comprehensive documentation for models and processes Monitor and support deployed solutions to ensure they meet performance expectations Actively seek out information and internal solutions to ensure reusability and adoption of common technologies Our expectations 3+ years of experience in the Field. Previous software engineering experience is preferrable Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data). Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics. Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle. Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes. The ability to design solutions using common design patterns and various design tools. Experience in experiment design and the ability to validate the credibility of information from various sources. A solid understanding of the business value of delivered features. Strong problem-solving skills, with an emphasis on using technical facts and reasoning. Excellent communication and collaboration skills, including active listening and the ability to build consensus. A strong drive for continuous self-development and a collaborative mindset for contributing to communities. Ability to balance quality and speed depending on the case, and justify your decision Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers English communication skills 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 inDrive's Forecasting product turns large-scale marketplace data into daily and monthly forecasts of the company's core supply, demand and financial metrics. These forecasts are the backbone of target setting, financial planning and scenario analysis for business teams and leadership. We are looking for a Senior Analyst to own this product: the quality and credibility of the numbers, the planning processes they feed, and the story behind every deviation. You will take over a working production solution (Python, BigQuery) and keep it reliably serving the business — but the core of the role is not modeling for its own sake. It is understanding how the business works: how pricing, incentives, marketing and market events move metrics, how those metrics connect to each other, and what decision-makers need from a forecast to plan with confidence. Key Responsibilities Business & planning Own the forecast as a decision-making product: track plan vs actual, decompose variances into business drivers (seasonality, pricing, incentives, marketing, external events), and explain in business terms why the numbers changed Support company planning cycles: provide forecast baselines for target setting and budgeting, and align assumptions with finance and business stakeholders Build and run scenario ("what-if") analysis for planned interventions: pricing changes, incentive and marketing spend, product launches, market expansion Maintain the dependency logic connecting supply, demand and financial metrics, so that forecasts stay mutually consistent and aggregate correctly across markets Translate ambiguous business questions into measurable forecasting problems; communicate assumptions, uncertainty and limitations clearly to both business and technical audiences Forecast production Run and monitor recurring daily and monthly forecasts: data completeness, sanity checks, run-over-run drift Investigate anomalies end to end — from inputs and business transformations to forecast outputs — getting to the business reason, not just a technical fix Improve models pragmatically: baselines, honest validation, and model choices driven by measurable planning value rather than sophistication. Keep the solution maintainable: readable Python, documentation, versioned changes Skills, Knowledge and Expertise 4+ years in analytics, forecasting or planning roles — for example marketplace or product analytics, demand planning, or decision science Strong understanding of how a business is planned: plan/fact cycles, target setting, driver-based models, unit economics. You see business metrics as a connected system, not as isolated time series Practical command of time-series forecasting — seasonality, holidays, external regressors, structural breaks, missing data — enough to own and improve production models Confident Python (pandas ecosystem): able to maintain and extend an existing production codebase Advanced SQL and experience with large datasets in a cloud data warehouse Rigorous validation habits: appropriate baselines, no data leakage, error metrics tied to business impact Ownership mindset: comfortable investigating issues across data, model, and integration boundaries Professional working proficiency in English and the ability to defend a number in front of senior stakeholders Nice to have: Background in mobility, marketplaces or other supply-and-demand systems Experience supporting financial planning, S&OP or budgeting processes Econometrics and causal inference; marketing-response models (adstock, saturation, investment payback) Hierarchical forecasting across multiple markets Experience owning or supporting production batch pipelines; BigQuery, Git-based workflows, CI/CD Technology environment Python (pandas, NumPy, scikit-learn, Prophet), BigQuery, Databricks, Git and GitHub Actions. This is an analyst role in an engineering-friendly environment: you should be at home in this stack, but deep ML engineering is not the core of the job. 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 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 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.

Location: Almaty, Kazakhstan Workplace: hybrid You will lead analytics for our Intercity vertical — a core business driving long-distance travel across cities. This includes car-based rides as well as partner transportation networks such as buses and other regional operators. Your mission is to uncover opportunities for growth, optimize pricing and demand-supply balance, and help shape the future of intercity mobility for millions of users. You will manage a team that partners closely with product, operations, and marketing to improve unit economics, drive market expansion, and deliver a seamless experience for both passengers and drivers. From building forecasting models and demand-planning tools to analyzing new market entry strategies and measuring the impact of promotional initiatives, your work will directly influence business-critical decisions. In this role, you will act as a trusted advisor to product and business stakeholders — aligning analytics with strategic priorities, driving data-informed decisions, and creating scalable processes for the fast-growing Intercity vertical. Key Responsibilities Lead, mentor, and develop the analytics team, supporting performance, growth, and professional development Define and drive the analytics strategy, roadmap, and standards aligned with business and product objectives Oversee key metrics, experimentation, and analytical outputs to ensure quality, consistency, and impact Partner with product, engineering, and business leaders to embed data-driven decision-making across the organization Establish and continuously improve analytics processes, documentation, and governance Ensure data quality, integrity, and effective cross-team data collaboration Skills, Knowledge and Expertise 5+ years of experience in data analytics or data science 2+ years of people management, leadings of 5+ people Analytical mindset: structured and critical thinking, the ability to find a balance between the resources spent and the effect on the business Strong mathematical background with an emphasis on mathematical statistics, optimization theory, time series and causal inference Proficiency in Python and data analysis libraries Proficiency in SQL: ability to work with large amounts of data, write and optimize complex queries, create analytical data marts Experience in creating BI reports: Plotly / Redash / Tableau English: Professional Working Proficiency 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 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 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: Abu Dhabi, United Arab Emirates Workplace: hybrid About the role We are preparing the data foundation for our autonomous-driving work, and we are hiring the engineer who will start it. Today we collect street-level imagery and GPS tracks from vehicle cameras, including our own camera units with NVIDIA edge devices on board, and use them to update maps. Next comes a dedicated survey vehicle with a full sensor set: multi-camera, IMU, LiDAR. You will start with the imagery and map data pipelines we run today, and as the sensor platform arrives, you will build the pipelines that turn its data into training datasets for autonomous-driving models. Key Responsibilities Build the pipelines that move multi-sensor data (multi-camera video, IMU, LiDAR, GPS) from vehicles into cloud storage, synchronize and geo-reference the streams Own the storage layout and lifecycle for sensor data: partitioning, hot and archival tiers, cost control as volume grows Build validation and monitoring on the ingest path: incomplete uploads, missing or unsynchronized streams, vehicles that stopped producing usable data Prepare training datasets for autonomous-driving models: select data by location, route, and conditions, version datasets, and deliver them in the formats ML teams need Until then: take over and develop the current imagery and GPS-track pipelines from vehicle cameras, and contribute to geodata pipelines (ingestion from company data, OpenStreetMap, Overture Maps and vendors, conflation, validation, publication) Work with company data in BigQuery and keep spatial queries fast on large PostGIS and GeoParquet tables Skills, Knowledge & Expertise 4+ years in data engineering Experience with multi-sensor data from vehicles or robots: cameras, IMU or LiDAR, and keeping the streams in sync Experience preparing training datasets for computer vision or autonomous-driving models. Large volumes of binary or media data in object storage (S3 or GCS); distributed processing (Spark or equivalent) Hands-on experience with spatial data: PostGIS, GeoPandas/Shapely, coordinate reference systems, GPS tracks Strong Python and SQL; AWS or GCP, Docker, Kubernetes Nice to have Sensor data formats such as ROS2 bag, MCAP or point clouds Parquet, Delta or Iceberg; Databricks Argo Workflows or Airflow OpenStreetMap and Overture Map QGIS BigQuery 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: Cairo, Egypt Workplace: hybrid We are looking for a Senior Data Engineer to join one of the Data Platform teams that works with the Marketing, Growth, partner, and financial data domains. You will be working with cutting edge cloud technologies (GCP, AWS, BigQuery, Databricks, K8s) and building a large scale data infrastructure for analytics, machine learning, and streaming/CDC data delivery. Key Responsibilities Build and operate batch and streaming ingestion into a layered BigQuery DWH (raw → ODS → data marts) using Airflow, Debezium CDC over Kafka with protobuf, Pub/Sub, and Dataflow Integrate external data sources end-to-end — marketing platforms (GA4, AppsFlyer, TikTok/Meta/Google Ads), payment providers, S3 buckets, and third-party APIs — including schema contracts, backfills, and reconciliation Engineer the data platform itself in Python: custom Airflow operators and connectors in a shared ETL framework, Kafka Connect on Strimzi (K8s), Cloud Functions, and API integrations with external providers Build CI/CD and change-management tooling for BigQuery: GitHub-based test-and-approval flows, SQL migration engines (Liquibase/Flyway/Bytebase), sandbox validation, backup and rollback Own reliability and correctness of pipelines: idempotency, deduplication, late-data handling, backfill and replay, freshness monitoring and alerting; write integration and unit tests Drive data governance and compliance: ITGC-compliant change management for BigQuery, IAM and least-privilege access, PII policy tags and DLP, Unity Catalog on Databricks, column-level lineage (OpenMetadata/Dataplex), and disaster-recovery planning Build internal data tools and platform services for agentic workflows with data — Streamlit apps, Slack bots, LLM-based agents and MCP servers that help teams find and use data Support analysts and business teams with data requests, fostering data-driven decision-making across the company Contribute to system design and architecture with the development team Skills, Knowledge and Expertise Strong practical Python: clean, well-structured, and tested code for services, tooling, and data pipelines Solid software design skills (OOP, modularity, design patterns) — we build platform tools for agentic workflows with data and plan to develop data-related backend services, so well-designed code is highly valued Experience building and operating services in a cloud environment (GCP, AWS or similar): CI/CD, containerization, monitoring and alerting Familiarity with Kubernetes and Terraform — our infrastructure runs on GCP/K8s Hands-on experience with DWH-related tasks (BigQuery or another cloud warehouse) and confident working SQL Clear communication with non-engineering stakeholders — a meaningful share of the work is data requests from analysts and business teams Demonstrated ability to take ownership of technologies or services and proactively contribute ideas to the team Nice to have Advanced SQL: complex queries, window functions, partitioning, clustering, and cost optimization Experience building reliable pipelines around CDC (e.g., Debezium): idempotency, schema evolution, backfills, and reconciliation Analytical data modeling skills: table grain, facts vs dimensions, slowly changing dimensions, and metric definitions Experience with stream processing frameworks such as Flink or Apache Beam/Dataflow Exposure to data governance and audit compliance (ITGC/SOX), Databricks Unity Catalog, or lineage/catalog tooling (OpenMetadata, Dataplex) Interest in building LLM-based agents and AI tooling for data 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’ll be responsible for auditing and hardening cloud and bare-metal systems, securing CI/CD pipelines, and designing robust security controls for our Kubernetes-based environments. This role requires deep technical expertise in cloud security (AWS), infrastructure as code, and vulnerability management, as well as the ability to collaborate on architectural decisions and drive security improvements across infrastructure layers.. Key Responsibilities Perform regular security audits across cloud, bare-metal, CI/CD, auth systems, and logging infrastructure. Support external security audits and penetration tests; manage remediation of findings and misconfigurations. Contribute to architectural design of infrastructure services, providing security expertise throughout the lifecycle. Build and maintain vulnerability scanning processes using commercial and open-source tools; support remediation efforts. Maintain and evolve the internal security infrastructure using AWS, Kubernetes, and modern DevOps practices. Skills, Knowledge and Expertise 3+ years of hands-on experience in infrastructure security, including vulnerability management across cloud and on-prem environments. Proficiency with cloud platforms (especially AWS) and Kubernetes, including applying security best practices and managing secure infrastructure. Strong knowledge of IaC tools (Terraform, Terragrunt, Ansible) and CI/CD pipeline security, using tools like GitHub Actions or GitLab CI. Automation skills using scripting languages such as Python or Bash, with experience building tools and scripts to improve security operations. Familiarity with security compliance and monitoring, including secret management (e.g., Vault), SIEM tools, and standards like ISO 27001 or PCI DSS. 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 70 700 EUR gross Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid We’re looking for an Engineering Manager to lead our Grocery team . In this role, you'll play a key role in building high-performance, scalable systems while leading and mentoring a strong engineering team. Key Responsibilities Lead and grow engineering teams, supporting new developers' adaptation and career development Manage project planning, execution, and resource allocation to ensure high-quality and on-time software delivery Align engineering efforts with business goals through close collaboration with stakeholders Develop and optimize engineering processes, tools, and technologies in collaboration with the team Build and nurture a developer community within the company and participate in external conferences Oversee the use of core technologies, including Golang, Python, MySQL, Kubernetes to ensure efficient development practices Skills, Knowledge and Expertise Demonstrated experience in engineering management with a strong background in software development Solid understanding of high-volume projects, server and client architecture, and development limitations Excellent leadership and communication abilities, with a talent for explaining complex technical concepts by sharing your technical expertize Ability to manage multiple projects simultaneously, ensuring timely and quality delivery Enthusiasm for new technologies and a commitment to ongoing skill development and teamwork BS/MS in Engineering, Computer Science, or a related field Experience working on Grocery, Marketplace, or other e-commerce products, with a strong understanding of their business and technical challenges 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 90 700 EUR gross Final benefits may vary depending on the location.

Location: Lima, Peru Workplace: hybrid We are looking for a Senior AdOps Specialist to architect and scale the advertising ecosystem for our global multi-vertical platform. This role is not just about trafficking; it is a growth-focused, technical leadership position designed for a professional who has managed massive scale at "Big 5" holding companies and top-tier publishers. You will bridge the gap between our Real-Time Deal (RTD) marketplace mechanics and a sophisticated Mobility Media Network (RMN), ensuring every ad impression delivers measurable incremental value. Key Responsibilities Enterprise-Scale Campaign Operations End-to-End Orchestration: Lead the launch and pacing of complex, multi-market campaigns across inDrive’s core ride-hailing and urban services verticals. Platform Mastery: Manage high-volume inventory using Google Ad Manager 360 (GAM360), ensuring precision in segmentation, targeting, and delivery. Retail Media Integration: Implement “digital shelf” strategies to optimize both on-site (in-app) and off-site (social/DSP) conversions. Quality Assurance: Establish rigorous "Big 5" agency-standard QA protocols to ensure 100% accuracy in tracking, brand safety, and creative rendering. Technical Implementation & Automation Workflow Engineering: utilize Python, SQL, and Scrapy to automate manual reporting tasks and audit partner revenue-share models for maximum profitability. Stack Management: oversee the integration of mobile monetization tools and coordinate technical needs with engineering teams for custom ad-product launches. Data Architecture: build advanced dashboards in Looker Studio and Redash that translate raw event data into actionable growth insights. Performance & Yield Optimization Strategic Experiments: execute continuous A/B testing on creative assets and landing pages to improve CTR and user behavior metrics across high-budget campaigns. Yield Management: monitor supply-side health, including fill rates, eCPM, and floor pricing, to maximize revenue without compromising the user experience of the inDrive app. Growth Consulting: act as an internal consultant for new product launches, adapting funnel structures for B2B AI startups or retail partners within the inDrive ecosystem. Qualifications 4+ years of experience in digital advertising, working with leading DSPs (The Trade Desk, DV360, Meta, TikTok) or publishers (500k+ DAU). Deep familiarity with marketplace-led advertising and last-mile conversion metrics. Strong business-oriented mindset, with understanding of the full campaign lifecycle, from commercial agreements and IOs through to campaign delivery, reporting, and post-campaign reconciliation. Strong understanding of web and app technologies (JavaScript, Flutter) with hands-on experience in ad tag implementation (GAM, GPT, native ads, HTML5 creatives). Experience with the ad request lifecycle, rendering, and click tracking. Experience debugging and troubleshooting ad delivery issues, including working with network logs, browser developer tools, and proxy tools such as Charles Proxy. Proficiency in Excel/Google Sheets for analysis and reporting. SQL is a plus. Google Ad Manager (GAM360) certification. Nice to have: Experience with mobile ad integrations (Android/iOS) using SDKs (e.g., Google Mobile Ads SDK). Hands-on experience independently implementing ad integrations across both web and in-app environments. 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 We are looking for a data-driven Operations & Revenue Manager to own marketplace performance, pricing effectiveness, and revenue optimization across international markets. In this role, you will be responsible for managing supply-demand balance, optimizing pricing and incentive levers, and driving sustainable, profitable growth at the city and country level. You will act as a key business owner for market performance, working closely with Analytics, Product, Finance, and Regional Operations to translate data insights into concrete operational and pricing actions. Key Responsibilities Marketplace Performance Ownership Own end-to-end performance of assigned markets or order types against key KPIs (growth, revenue, utilization, margins etc). Monitor market or order type health through core marketplace metrics and identify performance gaps, risks, and opportunities. Drive corrective actions and optimization initiatives to improve efficiency and profitability. Pricing & Revenue Optimization Define, test, and optimize pricing levers based on local market dynamics and business objectives. Evaluate pricing impact on rider behavior, supply engagement, and overall marketplace balance. Partner with Product and Analytics to implement pricing logic and ensure correct execution in systems. Supply & Demand Management Analyze supply-demand dynamics to maintain a healthy and efficient marketplace. Recommend actions to improve availability, utilization, and service reliability. Coordinate with regional operations teams to adapt strategies to local constraints and conditions. Analytics & Decision Support Use data and dashboards to track performance, diagnose issues, and inform decision-making. Partner with Finance and Analytics on investment analysis, market business cases, and performance reviews. Prepare clear, structured insights and recommendations for senior stakeholders. Cross-Functional Collaboration Act as a key interface between Operations, Product, Analytics, Finance, and Regional teams. Align stakeholders around priorities, timelines, and expected outcomes. Drive execution of cross-functional initiatives from problem definition to post-implementation review. Skills, Knowledge & Expertise 2+ years of experience in operations, revenue management, strategy, analytics, or consulting (marketplace or mobility experience is a strong plus). Strong analytical skills and experience working with large datasets to drive business decisions. Proficient in Excel and SQL; experience with BI tools (Power BI, Tableau) required; Python is a plus. Solid understanding of unit economics, pricing mechanics, and marketplace dynamics. Comfortable owning ambiguous problem spaces and driving decisions in a fast-paced environment. Strong stakeholder management and communication skills. Structured thinker with a bias toward execution and measurable impact. 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 64 700 EUR gross. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid inDrive is seeking an Anti-fraud Officer to own detection and investigation of fraud across our ride-hailing, delivery and city-to-city products: Ban evasion through multi-accounting, GPS spoofing, ride manipulation, promo and referral abuse, payment fraud, driver–passenger collusion etc. Key Responsibilities Analyze transactional and behavioral data using SQL and Python to identify suspicious patterns and emerging fraud schemes Develop, tune, and improve fraud detection rules and anti-fraud dashboards Evaluate the quality and effectiveness of detection rules by tracking precision and other key performance metrics Manage fraud cases end-to-end , from identifying suspicious activity to investigation, documentation, and escalation of confirmed incidents Conduct risk assessments of new and existing product features in collaboration with Product teams Analyze and monitor fraud losses , identify key sources of losses, and develop plans to reduce them Propose and implement fraud risk mitigation measures together with Product and other cross-functional teams Skills, Knowledge and Expertise 4 + years of experience in anti-fraud, risk analytics, or a related analytical field Strong proficiency in SQL and Python for analyzing large datasets Solid understanding of statistics and the ability to apply statistical methods to behavioral analysis and anomaly detection Experience working with data and the ability to independently identify suspicious patterns and formulate hypotheses Strong analytical thinking, attention to detail, and a structured approach to investigations Ability to work in ambiguous environments and independently drive investigations from initial detection to actionable conclusions and recommendations English — B2 or higher 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 70 700 EUR gross. Final benefits may vary depending on the location.