Вакансии

Location: United Kingdom Workplace: remote About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote , this role requires occasional visits to the Bristol office or London. About the Role Intermedia is looking for a Data Scientist to join our AI Data Science team. In this role, you will develop and apply advanced machine learning, generative AI, and statistical techniques to improve the intelligence, effectiveness, and reliability of Intermedia's digital agents. You will work on challenging problems involving large language models, retrieval, agent behavior, experimentation, evaluation, and optimization to help create digital agents that can understand customer needs, access relevant knowledge, and successfully complete complex tasks. You will work closely with AI/ML engineers, software engineers, product managers, and other data scientists to take ideas from experimentation through production. You will have significant ownership of data science solutions while helping establish strong practices for measuring and continuously improving the quality of our AI-powered experiences. What You Will Be Doing Machine Learning & Agent Intelligence Develop, evaluate, and improve machine learning and generative AI solutions that power Intermedia's Digital Agent Platform. Apply large language models (LLMs), natural language processing, retrieval, and other advanced AI techniques to improve agent understanding and performance. Develop approaches that improve agent reasoning, tool selection, knowledge retrieval, context management, personalization, and task completion. Experiment with model, prompt, retrieval, and agent configuration strategies to identify approaches that deliver the best customer and business outcomes. Evaluate commercial and open-source models and recommend appropriate approaches based on quality, latency, scalability, and cost. Generative AI & RAG Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions that ground digital agents in relevant enterprise and customer information. Develop and evaluate embeddings, retrieval strategies, ranking approaches, semantic search, and other knowledge-retrieval techniques. Build and refine end-to-end pipelines that combine LLMs with retrieval systems, enterprise knowledge sources, and agent workflows. Develop approaches to improve the relevance, accuracy, and consistency of AI-generated responses. Identify and mitigate issues such as hallucinations, poor retrieval, inappropriate responses, and other failure modes in generative AI applications. Evaluation & Experimentation Develop rigorous evaluation frameworks for measuring digital agent quality, including accuracy, relevance, task completion, reliability, safety, and customer experience. Design offline and online experiments to compare models, prompts, retrieval strategies, agent configurations, and other AI approaches. Apply statistical analysis, hypothesis testing, segmentation, and other quantitative methods to evaluate AI performance and identify opportunities for improvement. Define appropriate metrics and benchmarks that connect model and agent performance to customer and business outcomes. Analyze production behavior and feedback to identify patterns, failure modes, and opportunities to continuously improve digital agents. Ensure data and model quality through comprehensive testing, validation, and performance evaluation. Data & Solution Development Gather, preprocess, analyze, and model large volumes of structured and unstructured data from multiple sources. Use Python, SQL, Spark, and other relevant technologies to build scalable analytical and machine learning solutions. Develop features, datasets, and analytical approaches that support model development, experimentation, and evaluation. Partner with data and engineering teams to build and maintain reliable pipelines for model training, evaluation, and production use. Contribute to scalable ML/AI pipelines that support experimentation, deployment, monitoring, and continuous improvement. Ensure solutions are reproducible, maintainable, and designed to operate effectively at production scale. Collaboration Partner with Product, AI/ML Engineering, Software Engineering, and other Data Science team members to translate customer and business problems into effective AI solutions. Communicate analytical findings, model performance, tradeoffs, and recommendations clearly to technical and non-technical stakeholders. Participate in technical and design reviews and help establish strong practices for AI experimentation, evaluation, and model development. Mentor and support less experienced data scientists and contribute to knowledge sharing across the team. What You Will Bring to the Role Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Machine Learning, Analytics, or a related quantitative field; Master's degree preferred. 4+ years of professional experience in data science, machine learning, applied AI, or a related analytical field. Strong experience developing and applying supervised and unsupervised machine learning models to real-world problems. Hands-on experience with generative AI, large language models, NLP, or other modern AI technologies. Strong programming skills in Python and experience with SQL and large-scale data processing technologies. Experience with modern machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies. Strong understanding of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance measurement. Experience working with large volumes of structured and unstructured data. Demonstrated ability to independently frame ambiguous problems, develop analytical approaches, evaluate alternatives, and deliver actionable solutions. Experience taking machine learning or AI solutions beyond experimentation and contributing to their deployment and operation in production environments. Understanding of model quality, data quality, bias, reliability, and other considerations associated with production AI systems. Strong problem-solving and analytical skills with the ability to connect technical results to customer and business outcomes. Strong written and verbal communication skills with the ability to explain complex analytical and AI concepts to technical and non-technical audiences. Ability to collaborate effectively across Data Science, AI/ML Engineering, Software Engineering, Product, and business teams. Diversity, Inclusion, and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Location: Portugal Workplace: remote About Intermedia Are you looking for a company where YOUR VOICE is heard? Where can you MAKE A DIFFERENCE? Do you THRIVE in a FAST-PACED work environment? Do you wake every morning EXCITED to work with GREAT PEOPLE and create SUCCESS TOGETHER? Then Intermedia is the place for you. Intermedia has established itself as a leading provider of cloud communications and collaboration tech that allows companies to connect better. We have a strong track record of growth, profitability, and creating an environment where everyone matters. Everyone. While we are fast-paced and admittedly a bit intense, we promise that you won’t be bored. You will find Intermedia is a place where you can indulge your passion for creating and supporting great cloud technology. What’s more, we always look to promote from within and have many employees who have been with us 10, 15, and 20+ years! Culture at Intermedia is built on teamwork and transparency. We hold each other accountable and always have each other’s back! While primarily remote , this role requires occasional visits to the office in Coimbra or in Aveiro. We plan to open an office in Porto in the future. This approach gives team members the flexibility to work remotely while also coming together in the office for collaboration and teamwork. About the Role Intermedia is looking for a Data Scientist to join our AI Data Science team. In this role, you will develop and apply advanced machine learning, generative AI, and statistical techniques to improve the intelligence, effectiveness, and reliability of Intermedia's digital agents. You will work on challenging problems involving large language models, retrieval, agent behavior, experimentation, evaluation, and optimization to help create digital agents that can understand customer needs, access relevant knowledge, and successfully complete complex tasks. You will work closely with AI/ML engineers, software engineers, product managers, and other data scientists to take ideas from experimentation through production. You will have significant ownership of data science solutions while helping establish strong practices for measuring and continuously improving the quality of our AI-powered experiences. What You Will Be Doing Machine Learning & Agent Intelligence Develop, evaluate, and improve machine learning and generative AI solutions that power Intermedia's Digital Agent Platform. Apply large language models (LLMs), natural language processing, retrieval, and other advanced AI techniques to improve agent understanding and performance. Develop approaches that improve agent reasoning, tool selection, knowledge retrieval, context management, personalization, and task completion. Experiment with model, prompt, retrieval, and agent configuration strategies to identify approaches that deliver the best customer and business outcomes. Evaluate commercial and open-source models and recommend appropriate approaches based on quality, latency, scalability, and cost. Generative AI & RAG Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions that ground digital agents in relevant enterprise and customer information. Develop and evaluate embeddings, retrieval strategies, ranking approaches, semantic search, and other knowledge-retrieval techniques. Build and refine end-to-end pipelines that combine LLMs with retrieval systems, enterprise knowledge sources, and agent workflows. Develop approaches to improve the relevance, accuracy, and consistency of AI-generated responses. Identify and mitigate issues such as hallucinations, poor retrieval, inappropriate responses, and other failure modes in generative AI applications. Evaluation & Experimentation Develop rigorous evaluation frameworks for measuring digital agent quality, including accuracy, relevance, task completion, reliability, safety, and customer experience. Design offline and online experiments to compare models, prompts, retrieval strategies, agent configurations, and other AI approaches. Apply statistical analysis, hypothesis testing, segmentation, and other quantitative methods to evaluate AI performance and identify opportunities for improvement. Define appropriate metrics and benchmarks that connect model and agent performance to customer and business outcomes. Analyze production behavior and feedback to identify patterns, failure modes, and opportunities to continuously improve digital agents. Ensure data and model quality through comprehensive testing, validation, and performance evaluation. Data & Solution Development Gather, preprocess, analyze, and model large volumes of structured and unstructured data from multiple sources. Use Python, SQL, Spark, and other relevant technologies to build scalable analytical and machine learning solutions. Develop features, datasets, and analytical approaches that support model development, experimentation, and evaluation. Partner with data and engineering teams to build and maintain reliable pipelines for model training, evaluation, and production use. Contribute to scalable ML/AI pipelines that support experimentation, deployment, monitoring, and continuous improvement. Ensure solutions are reproducible, maintainable, and designed to operate effectively at production scale. Collaboration Partner with Product, AI/ML Engineering, Software Engineering, and other Data Science team members to translate customer and business problems into effective AI solutions. Communicate analytical findings, model performance, tradeoffs, and recommendations clearly to technical and non-technical stakeholders. Participate in technical and design reviews and help establish strong practices for AI experimentation, evaluation, and model development. Mentor and support less experienced data scientists and contribute to knowledge sharing across the team. What You Will Bring to the Role Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Machine Learning, Analytics, or a related quantitative field; Master's degree preferred. 4+ years of professional experience in data science, machine learning, applied AI, or a related analytical field. Strong experience developing and applying supervised and unsupervised machine learning models to real-world problems. Hands-on experience with generative AI, large language models, NLP, or other modern AI technologies. Strong programming skills in Python and experience with SQL and large-scale data processing technologies. Experience with modern machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies. Strong understanding of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance measurement. Experience working with large volumes of structured and unstructured data. Demonstrated ability to independently frame ambiguous problems, develop analytical approaches, evaluate alternatives, and deliver actionable solutions. Experience taking machine learning or AI solutions beyond experimentation and contributing to their deployment and operation in production environments. Understanding of model quality, data quality, bias, reliability, and other considerations associated with production AI systems. Strong problem-solving and analytical skills with the ability to connect technical results to customer and business outcomes. Strong written and verbal communication skills with the ability to explain complex analytical and AI concepts to technical and non-technical audiences. Ability to collaborate effectively across Data Science, AI/ML Engineering, Software Engineering, Product, and business teams. Diversity, Inclusion, and Equal Opportunity We hire, promote, and compensate employees based on their ability to perform their job responsibilities, without regard to race, color, creed, religion, sex, gender, marital status, national origin, ancestry, age, citizenship, physical or mental disability, sexual orientation, or any other basis protected by applicable law (collectively referred to in our Code of Conduct as “Protected Classes”). We do not tolerate employment discrimination in the workplace, and we are committed to making reasonable accommodations for identified disabilities or other limitations as required by all applicable laws. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Location: London, United Kingdom Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Data Science organisation sits at the heart of Deliveroo powering decision-making across our 3 sided marketplace. Our Analytics community is highly active, with guest lecturers, study groups, mentorship programmes and a robust technical review process. Our data scientists come from all kinds of backgrounds but have excellence in common. We’re looking for a Senior Data Scientist to join our London team (working hybrid, 3 days in the office). In this role, you’ll enable high-quality human-led decision-making to maximise impact. What You’ll Be Doing As a Senior Data Scientist at Deliveroo, your goal is to maximise business impact within one of our product areas. A core part of the role is designing, running and interpreting experiments, and using causal inference to guide product decisions in complex, real-world settings. You will go beyond simply answering “did this feature work?” and instead focus on understanding what the true impact is, why it worked or did not work, and how results generalise across users, markets and time. Here’s what your day-to-day might look like: Driving Strategy/insights through Experimentation: Leading the design of both simple and complex experiments and proactively translating findings into strategic direction. Master Causal Inference : Apply advanced techniques to estimate long-term and heterogeneous treatment effects. Drawing reliable conclusions in settings with selection bias or imperfect randomisation. Drive Deep Product Insights: Uncover the fundamental drivers of experiment performance, determining why features succeed and how results generalise across different users, markets, and timeframes. Using insights from past experiments to improve future decision-making . What You’ll Need to Thrive Strong experience designing, running and interpreting A/B experiments in production environments Solid understanding of causal inference concepts Ability to apply statistical thinking to messy, real-world product problems, not just ideal experimental setups Great communication skills in person, in writing and in code, with both technical and non-technical audiences A problem solver with a deep analytical mindset Ability to think creatively and insightfully about business problems Familiarity with SQL Excellent people skills as you will be meeting with stakeholders to translate business needs into data science problems Why Join Us? At Deliveroo, you’ll do work that matters, solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. ​​💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. We aim to create a fair process that lets your skills shine—our interview typically includes 3-4 stages. Find more about how we hire here . Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Задачи: сбор и уточнение требований от маркетинговых аналитиков и BI, их перевод в изменения логики атрибуции, источников и data marts; миграция attribution-пайплайна (dbt-модели, Airflow DAGs, источники) на core DWH-платформу с параллельным прогоном старого и нового контуров и сверкой до переключения;

Location: Intellias Meet your recruiter Kateryna Zemetska kateryna.zemetska@intellias.com https://www.linkedin.com... Vacancy details Data Engineering Data Engineer Senior Bulgaria, Croatia, Poland, Portugal, Spain, Ukraine Remote APPLY NOW REFER A FRIEND Dive deep into Digital! For more than 20 years Intellias has been developing top-tier digital solutions for the world’s leading companies, keeping them in line with the latest technology trends. Join in and provide innovations for the future! What project we have for you For an innovative AI project in the retail sector, we are seeking an experienced AI Engineer to support the development and implementation of an AI-powered pricing model. The aim of the project is to link internal and external data sources and, using machine learning and neural networks, generate dynamic, AI-based price recommendations for individual items. This is intended to optimise pricing decisions and unlock additional margin potential. The technological foundation is a prototype that has already been successfully developed and implemented by international colleagues in collaboration with Microsoft. The existing solution is to be transferred to the company’s own data environment, adapted and further developed. The data model, as well as existing Python code and notebooks within Azure Databricks, are already in place. Working alongside the in-house data science team, you will be responsible for developing, training and validating a proprietary AI model based on these resources. As the project progresses, the solution will be integrated with the ERP system to provide automated price and terms suggestions for operational staff. What you will do Further development and customisation of an existing AI pricing prototype based on Azure Databricks Analysis and processing of internal and external data sources Development and implementation of neural networks and machine learning models Development, training and validation of proprietary AI models Implementation and optimisation of AI models using Python Use and processing of Large Language Models (LLMs) and prompt engineering Porting existing models to the company’s own data and system landscape Collaboration with the internal data science team and international project stakeholders Supporting the integration of the developed solution into the existing ERP system What you need for this At least 2–3 years’ practical project experience in AI engineering or similar AI projects Very good knowledge of Azure Databricks Strong knowledge of Python Substantial experience in machine learning and deep learning Practical experience in the development, training and validation of neural networks Experience working with Large Language Models (LLMs) and prompt engineering Experience in the development and implementation of AI models in real-world business environments Ability to translate business requirements into technical models and solutions Good communication skills in English and German Ability and desire to travel to client office (Germany) An independent and structured approach to work Will be a plus: Experience in the retail sector Experience with pricing models and predictive analytics Experience integrating AI solutions into ERP systems What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Databricks English German Python

💎 Полный цикл анализа триггерных кампаний, пилотов и A/B-тестов: настройка кампаний в CRM, контроль корректности, согласование методики оценки эффективности, анализ воронки коммуникаций и влияния на продажи и маржу.

Location: Hamburg Workplace: Hybrid adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually. Architecting Intelligence to Optimize 200M+ Daily Decisions As the intelligence core of our engineering organization, our Data Science team doesn't just deploy models, we engineer the fundamental decision engine that powers our platform. At a scale of 770 million users and 100,000+ predictions per second, we are solving a multi-objective optimization problem that balances user incentives, advertiser ROI, and long-term platform health in real time. Our architecture is built on a 1PB+ behavioral data lake, providing the high-fidelity input necessary to train deep learning models that predict individual user engagement with precision. We aren't just optimizing clicks, we are dynamically calculating optimal reward structures to sustain a global value exchange. Engineered for performance, our stack leverages PyTorch for model training, NVIDIA Triton to achieve sub-100ms inference. We own the full ML lifecycle from high-level research and feature engineering to deployment and A/B experimentation. Here, you will find the autonomy, the data depth, and the massive scale required to solve the most complex optimization challenges in the adtech ecosystem. The data infrastructure behind this runs at real scale: 2TB ingested in real time every day, 100+ Airflow jobs and data pipelines, and ML models handling p99 latency of 100ms across 100,000+ predictions per second. Your Mission & Who We Are Looking For - Quantitative Academic Foundation: You are currently pursuing a Bachelor’s or Master’s in Data Science, Computer Science, Mathematics, Statistics, or a related quantitative field. You are available to contribute up to 20 hours per week during the semester. - ML Model Prototyping: You will support the research and evaluation of deep learning and machine learning models that predict user behavior across our 770 million user base. We are looking for solid Python skills and hands-on familiarity with PyTorch, TensorFlow, scikit-learn, and gradient boosting libraries (LightGBM/CatBoost/XGBoost) to prototype new algorithms. - Large-Scale Data Exploration: Operating on our 1PB+ behavioral data lake, you will extract patterns from terabytes of data to engineer high-fidelity features for our training pipelines. This requires strong SQL fundamentals, an interest in distributed query engines (AWS Athena, Trino, Spark), and fluency with pandas, polars, and NumPy. - Experimentation & Validation: You will collaborate closely with our data scientists to test your fit-for-purpose solutions against our multi-objective optimization problem. We need someone who can rigorously evaluate models through offline experiments and A/B tests before they hit our 100,000+ predictions-per-second production environment. - Plus: ML Infrastructure Exposure: Any prior exposure to the systems that run our real-time scale—AWS, workflow orchestration (Airflow), containerization (Docker), or basic model deployment workflows—will accelerate your impact. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. Skip writing cover letters. Tell us about your most passionate personal project, your desired salary, and your earliest possible start date. We are looking forward to your application! We welcome applications from people who will contribute to the diversity of our Company. We welcome applications from people who will contribute to the diversity of our company.

Отработка гипотез, создание форм отчетности, аналитика и проверка данных, аналитика показателей эффективности персонала: Анализ данных и поиск закономерностей в результатах проведенных исследований;

Location: Argentina; Brazil Workplace: Remote We're looking for an experienced and strategic Senior Data Analyst to join Uberall's product team. In this role, you’ll be at the heart of product decision-making, working closely with product managers on how we measure each product, whether launches work, and what the data tells us. Your skills in distilling complex data into meaningful narratives will be instrumental in supporting our growth and product innovation. If you’re passionate about using data to tell compelling stories, enjoy structuring insights that influence product decisions, and thrive in a collaborative environment, this could be the perfect role for you. Join us in creating exceptional experiences for our clients and helping shape the future of our products. Apply today to make a tangible impact with your data expertise! Your Responsibilities: - Build and maintain well-documented product data models in dbt, working within the BI team's shared standards and review process. - Act as the analytics point of contact for the Product data domain, working with domain owners and data partners to keep metric definitions and standards consistent across the company. - Build and maintain dashboards and reports that give product managers a clear, self-serve view of how their products are performing. - Define and monitor key product performance metrics with stakeholders, focusing on areas such as acquisition, retention, monetization, and adoption to drive product and business insights. - Collaborate with product managers, engineers, and cross-functional teams to prioritize features and drive a data-informed product roadmap. - Create clear, concise stories from data analyses, presenting findings to technical and non-technical audiences to inform product decisions and strategy. - Conduct in-depth analyses of user behavior, feature usage, and A/B test results to evaluate product changes and measure their impact on user engagement, retention, and revenue. - Analyze product usage trends to define activation metrics that increase customer lifetime value (LTV), and contribute product usage signals to churn prediction alongside data and Customer Success partners. - Shape the product analytics roadmap together with product managers, prioritizing the questions that matter most for each product area. - Mentor and support team members, promoting best practices in data analysis and effective communication across the organization. - Use AI-powered analytics tools and agentic workflows (LLM assistants, automations, AI product tracking) on top of our shared data platform to scale self-serve insights for product teams. Your Profile: - 5+ years of experience in data analysis, ideally with experience in or close collaboration with product teams in a SaaS or technology environment. - Advanced skills in BI and product analytics tools (e.g. Metabase, Pendo), and comfortable picking the right tool for each question. - Strong command of SQL, with the ability to create and optimize complex queries on large datasets. - Solid experience in data modelling (e.g. dimensional modelling, dbt or similar), designing clean, documented and reusable models that act as the single source of truth for product metrics. - Hands-on experience using AI tools (e.g. coding assistants, LLM-powered analytics) to accelerate query and model development, automate repetitive work and speed up insight generation, while keeping a critical eye on accuracy. - Proven ability to translate complex data insights into clear, actionable recommendations for cross-functional teams. - Hands-on experience with adoption analysis, A/B testing frameworks and statistical analysis, with a solid foundation in designing and analyzing experiments. - Proven experience in establishing and tracking core product metrics and driving insights that influence product development and growth initiatives. - Exceptional communication and presentation skills, adept at engaging and aligning stakeholders at all levels. - Highly organized, with strong prioritization skills to manage multiple projects and deadlines. - Comfortable working both independently and collaboratively in a dynamic, fast-paced environment. - Fluency in English is required; additional language skills are a plus.

Location: Москва Мы команда DS Департамент «Занять и сберегать» (Управление искусственного интеллекта и исследования данных), мы умеем быстро и качественно проверять гипотезы, строить ML-модели, консультировать бизнес, проводить A/B-тесты и защищать финансовые результаты. Вас встретит дружная команда, мощные кластеры, много данных и самое главное – интересные, амбициозные и сложные задачи. Мы разрабатываем и внедряем решения от идеи до вывода в промышленную эксплуатацию, включая исследования источников, построение витрин, разработку моделей и встраивание в существующую инфраструктуру исполнения моделей. У нас вы сможете поработать с действительно большими данными и внедрить решения масштаба страны, используя самый современный технологический стек. Обязанности Ключевые направления, в котором вы будете работать: * ценообразование * uplift-моделирование * задачи ранжирования * модели склонности * look-a-like * response модели * работа с регрессионными таргетами * кластерный и факторный анализ. Требования * опыт в части ML задач - не менее 1 года * опыт работы и глубокое понимание классического ML * продвинутые знания статистики и машинного обучения * опыт оценки качества результатов (DS и бизнес-валидация) * опыт проведения A/B-тестов * хорошие знания Python, SQL, Bash, PySpark. Будет плюсом: * опыт работы с Transformers * успехи в ML-соревнованиях, хакатонов * навыки работы с генеративными AI-моделями * опыт создания AI-агентов и использования их в работе будет преимуществом. Условия * работа в удобном и современном офисе недалеко от станции метро Кутузовская. * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Remote Workplace: Remote About Us Launched in 2019, Constructor is an AI-first e-commerce search and discovery platform that helps shoppers find the right products at the right time and enables leading global e-commerce brands to drive meaningful revenue and conversion gains. About the Team We build the AI agent that helps merchandisers, product managers, and executives grow their e-commerce business: it finds opportunities in their data, tailors insights to each person's role, and takes routine work off their plate by delivering answers where they already work. We are transforming how digital merchandising teams work: instead of digging through reports and configuring rules by hand, they ask in plain language, get answers grounded in their own data, and approve the changes the agent prepares. Customers already rely on the agent to save time and make better decisions. We own the agent end to end, from the first question a merchant asks to the answer they act on. We also own the analytics behind it: the pipelines and cubes for search, browse, and recommendation performance, and the metric definitions merchants rely on. That is why we build the agent and the Customer Dashboard as a platform that every Constructor team extends. We create the foundation that other teams build on: the agent framework, shared components, and infrastructure. On top of it, teams add their own data, tools, and skills, so the agent can answer questions in their domain and the dashboard can show their features without separate interfaces. Each new capability gives merchants more ways to grow their business. What you'll do - Build and own the batch pipelines and cubes behind dashboard analytics and agent insights - Model shopper, trend, and benchmark data so the agent can find opportunities across the shopping journey - Shape data for each role: a merchandiser's category, a product manager's funnel step, an executive's total - Own data quality and trust: freshness, monitoring, alerting, and metric definitions - Work with engineers, analysts, and product to find the data the agent is missing and turn merchant questions into data products - Ship your data into the product: simple analytics UIs, and the agent skills, tools, and prompts that use it Requirements Must-have - Proficiency in Python and SQL (any dialect) - Experience building and maintaining batch data pipelines with Spark (PySpark) - Familiarity with the big data stack: Databricks, ClickHouse and dbt - Experience with data modeling for analytics: aggregated tables and cubes that feed dashboards and APIs - Experience with data quality and pipeline monitoring: freshness checks, alerting, incident response - Ability to prototype fast and pick the metrics that matter in e-commerce - Ability to translate business questions into technical requirements, and back - Clear communication with engineers and non-technical stakeholders Nice-to-have - Experience building frontend UIs, or willingness to work across the full stack to ship data into product features - Experience with pandas, NumPy - Experience building AI agents: tools, skills, prompts, context, and evaluations - Experience with real-time analytics: ClickHouse, Cube.js - Experience with AWS - Familiarity with statistics for experimentation (A/B tests) Benefits - 🏝️ Unlimited vacation, with a recommended minimum of 3 weeks per year - 🌎 Fully remote team: choose where you live - 🛋️ Work-from-home stipend to set up your home office - 💻 Apple laptop for new employees - 🧑‍🎓 Annual training and development budget for every employee - 👪 Maternity and paternity leave for qualified employees - 🧠 Smart colleagues who help you grow and make a meaningful impact - 💵 Base salary: 80-120K USD, depending on knowledge, skills, experience, and interview results - 📈 Stock options, in addition to the base salary - 🎉 Regular team offsites to connect and collaborate Diversity, Equity, and Inclusion at Constructor At Constructor.io http://Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications. How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice https://constructor.com/recruitment-privacy-notice. After that period your data will be deleted or anonymized.

Location: Москва Workplace: Гибридный О компании Геоэффект — это аналитический сервис компании МТС, основанный на обработке обезличенных больших данных мобильного трафика и геопозиции абонентов. Он позволяет проводить детальный анализ населения, туристических потоков, посещаемости объектов и инфраструктуры с высокой точностью и частотой обновления. Сервис используется в различных отраслях, включая ритейл, банковскую сферу, туризм, транспорт, государственное управление и урбанистику, для оптимизации решений по размещению объектов, развитию инфраструктуры, анализу аудитории и повышению эффективности бизнес-процессов. Обязанности Выгрузки, обработка гео и телеком-данных (трафик, локации нахождения абонентов); Разработка простых ETL-процессов; Выполнение ADHOC-задач на PySpark; Создание сегментов пользователей; Подготовка отчетности, обработка таблиц на PySpark Требования В том числе Студенты бакалавриата, специалитета или магистратуры; Базовое знание SQL и Python; Знание основ Hadoop и PySpark будет большим плюсом Условия Собственную платформу MTS Ocean для получения ИТ-ресурсов, а это значит, что деплой, мониторинг, observability — не будут для тебя проблемой, ты сможешь сосредоточиться на фичах; Профессиональные гильдии инженеров, где мы поддерживаем друг друга и помогаем стать лучше; Внутреннюю площадку TechTalks для обмена опытом, дискуссий, развития навыков самопрезентации; Участие во внешних IT конференциях. Мы выступаем на HighLoad++, DataFest, Mobius, Test Driven Conf, Joker, DevOps, Матемаркетинг и даже проводим собственную конференцию по архитектуре True Tech Arch; Полезные курсы и вебинары в корпоративном университете и электронную библиотеку; ДМС с первого месяца работы, включая стоматологию; Страхование от несчастных случаев с 1 месяца работы. Материальную помощь в сложных жизненных ситуациях; Отпуск 28 календарных дней (+3 дополнительных дня за ненормированный рабочий день); Гибридный формат работы; Прием врачей общей практики и массаж в офисе; Мобильная связь за счет компании и льготные тарифы для близких; Подписка на онлайн-кинотеатр KION, сервис МТС Музыка, книжный сервис Строки от МТС, безлимитные мессенджеры и соцсети.

Задачи: — Развитие продукта, построение системы работы с данными, усиление процессов и консультирование бизнеса по вопросам точек роста. — Анализ игровой экономики, баланса, поведения игроков и других аспектов игрового продукта. Требования: — Опыт работы продуктовым или маркетинговым аналитиком не менее 2,5 лет, общий опыт в аналитике от 4 лет. — Высшее физико-математическое или техническое образование и/или быстрый карьерный рост в крупных продуктовых компаниях с большим объемом данных (например, Avito, Yandex, inDrive). — Уверенные технические навыки в SQL, Python, мощная математическая и статистическая база, опыт работы с AB-тестами. Условия: — Работа удалённо из любой страны, при этом у компании есть офисы в Армении, Грузии, Казахстане, Сербии, Кипре. — Использование современного технического стека: databricks, pyspark, AWS, Appsflyer, Amplitude, S3, Airflow, Redshift, Monte Carlo. — Аналитики работают с данными через SQL и Python в Jupyter/Databricks ноутбуках, создают прототипы дашбордов в Tableau.

Задачи: — Проектировать и разрабатывать дашборды и отчёты в BI-системах (Power BI, Superset) — Повышать долю процессов, покрытых ии-агентами или генеративными пайплайнами с использованием LLM — Обеспечивать наглядность и понятность представления данных для бизнес-пользователей — Формировать регулярную и ad-hoc отчётность Департамента — Поддерживать и развивать существующие отчёты и дашборды — Обеспечивать единые стандарты визуализации и дизайна отчётности — Участвовать в разработке и внедрении новых подходов к визуализации данных и отчётности — Управлять зависимостями, влияющими на своевременность построения отчётности (источники данных, доступы, смежные команды) Требования: — Уверенное владение SQL — Опыт работы с Python — Опыт работы с BI инструментами (Power BI или иные инструменты визуализации) — Знание LLM Условия: — Внутренние семинары, внутренние митапы — ДМС со стоматологией для сотрудников и скидка на покупку ДМС для ближайших членов семьи — Техника для комфортной работы — Сессии профессионального развития персонала с планом индивидуального развития каждого сотрудника

Location: Горно-Алтайск **Релокация на Алтай обязательна!** Курорт «Манжерок» — крупнейший инвестиционный проект в Росссии. Мы ищем системного аналитика, который станет связующим звеном между бизнесом, IT и данными. Ваша задача — превратить разрозненные данные о гостях в инструмент для роста выручки и улучшения сервиса. Вы будете отвечать за построение аналитической инфраструктуры, внедрение BI-отчетности и использование современных ИИ-инструментов для анализа дополнительных трат гостей. Обязанности ### Чем предстоит заниматься **Аналитика и отчетность:** * Сбор и формализация потребностей коммерческих и операционных подразделений. * Выстраивание системы показателей, витрин данных, регулярной отчетности и BI-дашбордов. **Работа с данными:** * Организация получения и объединения данных о гостях и их тратах из PMS, CRM, POS и других систем курорта. * Определение правил сопоставления транзакций с гостем и бронированием, контроль полноты и качества данных. **Бизнес-анализ и рекомендации:** * Анализ дополнительных трат по сегментам, услугам и этапам клиентского пути. * Выявление возможностей роста выручки и формирование практических рекомендаций для маркетинга, продаж и сервисных направлений. **Прогнозное моделирование:** * Построение, проверка и развитие прогнозных моделей для сегментных и персонализированных предложений (вероятность покупки, отклик, прогноз трат, повторный визит, LTV). **Внедрение ИИ:** * Внедрение процесса использования ИИ-агента для сбора и проверки данных по доп. тратам, классификации операций, выявления аномалий и подготовки выводов. **Маркетинг и CRM:** * Совместно с CRM и маркетингом: запуск и оценка сегментных предложений, измерение конверсии, доп. выручки и инкрементального эффекта. **Управление проектами:** * Управление взаимодействием с IT, владельцами систем и подрядчиками по интеграции данных, автоматизации и внедрению моделей. * Документирование метрик, правил расчета и процессов. Требования ### Наши ожидания * **Опыт**: от 3 лет в аналитике данных / бизнес-аналитике. * **Технические навыки:** * Уверенный SQL, опыт работы с витринами данных, ETL/ELT, BI-инструментами и контролем качества данных. * Python для анализа данных и моделирования (pandas, numpy, scikit-learn); понимание валидации моделей и интерпретации результатов. * **Предметная область**: опыт клиентской аналитики, сегментации, прогнозирования спроса и покупательского поведения, оценки эффективности персонализированных предложений. * **Понимание систем:** понимание архитектуры и интеграции PMS, CRM, POS и транзакционных источников. Опыт в гостиничном бизнесе, туризме или услугах будет преимуществом. * **ИИ-грамотность:** понимание возможностей и ограничений ИИ-агентов и LLM в аналитике, принципов проверки результатов и защиты клиентских данных. * **Soft skills:** навыки управления проектами, постановки задач IT и подрядчикам, презентации выводов руководству и бизнес-заказчикам. * Образование: высшее (математика, экономика, информационные технологии или смежные направления). ### Личные качества * Системное мышление. * Ответственность за результат. * Инициативность. * Внимательность к качеству данных. * Умение выстраивать взаимодействие между подразделениями. Условия ### Мы предлагаем * Возможность стать частью команды флагманского проекта туристической отрасли * **Компенсация аренды жилья**; * **Компенсация расходов на переезд**; * **ДМС со стоматологией;** * **Корпоративный трансфер** из г. Горно-Алтайска, с. Майма; * **Корпоративное питание** * Скидки на пользование услугами курорта: ски-пассы и байк-пассы, возможность аренды горнолыжного оборудования со скидкой, скидки в ресторанах и детском центре Курорта; * **Занятия по горным лыжам и сноуборду;** * Возможность получения льготного ипотечного кредитования; * Бесплатное подключение к системе «СберПрайм +», подписка на онлайн кинотеатр Okko

Location: Москва Мы создаем сервисы кредитования в Сбербанке, позволяющие клиентам быстро и удобно получать кредиты онлайн. Клиент может подать заявку на получение кредита через мобильное приложение или WEB, получить одобрение всего за две минуты и мгновенно перевести средства на свою банковскую карту или счет, без необходимости посещать отделение банка лично. Наш проект постоянно развивается. Мы планируем улучшать клиентский опыт и развивать наши сервисы внедряя механики динамического ценообразования. Работа в нашей команде позволит вам принять участие во всех этапах разработки высоконагруженных распределённых систем, начиная от проектирования и заканчивая внедрением в промышленную эксплуатацию. Вы сможете активно влиять на создание новых продуктов и улучшение существующих бизнес-процессов, применяя современные технологии и подходы. Возможность углублять знания и улучшать навыки в области современного программирования и управления проектами. Комфортные условия труда - современное оборудование и стабильность занятости в одной из крупнейших финансовых организаций страны. Присоединяйтесь к нашей команде и станьте частью инновационного процесса, создающего удобные решения для миллионов пользователей по всей России! Первый этап отбора на эту вакансию — общение с AI-рекрутером. После отклика ждите сообщение от него, диалог займёт примерно 10 минут. Задача AI-рекрутера — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. AI-рекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным для всех! Обязанности * исследование и разработка новых методов и алгоритмов машинного обучения * эксперименты в области глубинного обучения, обучения с подкреплением, байесовских методов, VAE и других прикладных направлений * исследование и применение современных NLP-методов: трансформеры, LLM API, LangChain * анализ данных для проверки исследовательских гипотез * проектирование и проведение экспериментов, оценка результатов * подготовка прототипов для тестирования новых подходов * анализ применимости новых методов к задачам компании * подготовка предложений по архитектуре моделей и выбору методов * подготовка отчётов и презентация результатов исследований. Требования * опыт работы на позиции Data Scientist / исследователя — от 2 лет, в том числе в исследовательских задачах * Python — уверенное владение, включая фреймворки для ML и DL: PyTorch, scikit-learn, pandas, numpy * SQL — составление запросов; опыт работы с PostgreSQL * глубокое знание классических и современных методов ML * понимание глубинного обучения, обучения с подкреплением, байесовских подходов, VAE * опыт проведения исследований: формулирование гипотез, дизайн экспериментов, статистическая оценка * математическое моделирование, статистика, системный анализ * опыт экспериментальной работы с NLP-моделями и трансформерами. Будет плюсом: * опыт работы с Hugging Face Transformers, LangChain, LLM API * опыт контейнеризации и запуска экспериментов в Docker * опыт работы с большими данными (PySpark, Hive, HDFS) * опыт работы в банковской / финансовой сфере * навыки работы с генеративными AI-моделями * опыт создания AI-агентов и использования их в работе * опыт использования GigaChat, Kandinsky и аналогов в продуктах * навыки создания и использования AI-агентов * инструментальное владение AI для анализа, генерации и автоматизации. Условия * гибридный формат работы (4 дня офис) на Кутузовском, 32к1 * ежегодный пересмотр зарплаты, квартальная и годовая премия * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Responsibilities: — Develop algorithms focused on women's hormonal health using AI-powered technology. — Translate complex hormonal data into actionable insights and product features. Requirements: — At least 3 years of experience in data science. — Proficiency in Python and SQL. — Experience working with health, wearable, or biomarker data. — Strong judgment in model validation. — Ability to communicate effectively with stakeholders. Benefits: — Remote work opportunity. Mira is a company transforming hormone health through AI-powered technology, helping individuals track and understand their hormones at every stage of life.

Location: Москва SberData - департамент по управлению данными всего Сбербанка. SberData строит централизованное хранилище данных - Корпоративную аналитическую платформу, объем которого превышает 100 ПБ. Это продуктово-ориентированная инженерная команда с функциями развития выделенных технологических направлений, отражающих новый подход Сбербанка к данным и к применению AI. Обеспечим развитие и интересные задачи в направлениях: работа над сопровождением крупных проектов хранилищ данных на базе Apache Hadoop и Kubernetes; Hadoop Ecosystem: Apache Spark, Hive, HBase, Kafka, NiFi; оптимизация процессов: Performance Tuning, улучшение SLA поставки данных; мониторинг качества данных, управление Мастер-данными и поддержание доступности платформ. Обязанности ### Задачи: * разбор и решение инцидентов по платформам и сервисам: Spark, Kafka, Hive, K8s * взаимодействие с разработчиками, бизнесом и 2-й линией * анализ причин проблем, выработка предиктивных мер и корректирующих действий * участие в приемо-сдаточных испытаниях прикладного ПО * исследование поведения системы, локализация дефектов, сопровождение патчей * консультации бизнес-пользователей и 2-й линии по вопросам работы с платформой. Требования ### Требования: * опыт работы Data Engineer / Support Engineer от 1,5 лет * уверенное владение SQL * опыт работы с СУБД (Oracle, PostgreSQL, Teradata) * знание клиент-серверных и микросервисных архитектур, понимание принципов построения интеграций через REST API * английский язык: чтение технической документации. ### Будет плюсом: * опыт работы со стеком Hadoop: Apache Hive, Spark, Kafka * python — для написания скриптов автоматизации * опыт создания дашбордов мониторинга: Grafana, Prometheus * опыт работы с продуктами Atlassian: Jira, Confluence * владение PSQL * понимание принципов функционирования хранилищ данных (OLTP/DWH) и систем хранения. Условия ### Условия: * комфортный современный офис: БЦ Даниловский форт, рядом с М.Тульская, Верхние котлы * **график работы – офис** * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.