Data Scientist вакансии

Location: Remote USA; Canada Workplace: remote ABOUT YOU We are looking for an accomplished Principal Machine Learning Engineer to join our global ML organization. In this role, you will drive innovation across our machine learning ecosystem, architect advanced ML solutions, and mentor junior ML engineers around the world. You will play a key part in shaping our technical direction—leading complex ML initiatives, elevating engineering standards, and guiding teams as they build scalable, production‑ready machine learning systems. If you are ambitious, energized by solving challenging technical problems, passionate about developing talent, and excited to influence the future of ML/AI in the video game industry, this could be the perfect role for you. ABOUT US   Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Requirements: Modeling Depth Advanced Degree in Statistics, machine learning or related areas. Experience in statistics/ML expertise with a track record of leading high-impact data science initiatives at scale of billions of transactions. Hands-on experience creating, training and fine-tuning models not just integrating hosted model APIs. You should be able to walk through  the data, the objective, what broke, and the before/after evaluation numbers, and why the model did not perform as expected. Experience owning models in production: deployment, monitoring, drift detection, retraining — with real latency budgets, not just research notebooks. Production experience with classical ML for fraud/anomaly detection, recommendation, or churn/LTV (gradient boosting, deep learning, graph-based models). Technology Familiarity Supervised learning, transfer leaning on machine learning as well as neural networks Basic LLM knowledge, especially how to use it and where not to use it. MLOps foundations: feature stores, experiment tracking, model registries (MLflow/W&B-class), continuous training pipelines. Model serving and inference optimization (vLLM-class serving, quantization). Nice-to-Have: Publications, conference talks, or recognized open-source contributions to training/eval tooling . Graph-based fraud detection (fraud rings, device/account linkage).. Gaming, payments,  fraud, advertising  domain experience. Hands-on, up-to-date experience with modern AI tools (e.g., Claude, Copilot, Cursor) for code generation, review, and accelerating day-to-day engineering work. Benefits: We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes 100% company-paid medical, dental, and vision plans, unlimited Flexible Time Off, and a personalized career roadmap for each US employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.   Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the Data Scientist position, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification   Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements   Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com.

Location: Athens; Limassol; Nicosia; Thessaloniki Workplace: hybrid The Role:  We are looking for a Senior Data Scientist specializing in Graph AI to join our growing Data Science team. In this role, you will design and deploy production-grade graph machine learning solutions, working with Graph Neural Networks (GNNs), graph databases, and large-scale datasets to solve complex real-world problems.   You will play a key role in shaping the company's Graph AI capabilities, collaborating with cross-functional teams and mentoring other data scientists while delivering innovative, business-impacting solutions. The main responsibilities of the position include: Design, develop, and deploy Graph Neural Networks (GNNs) and graph-based machine learning solutions Transform large, complex datasets into graph representations and extract actionable insights using advanced analytics, graph algorithms, and statistical techniques. Drive the adoption of Graph AI across the organisation by identifying new use cases and contributing to the evolution of the company's data science strategy. Communicate complex technical concepts and model outcomes clearly to both technical and business audiences. Ensure high standards in data preparation, feature engineering, model evaluation, documentation, and code quality . Leverage technologies such as Python, Graph Neural Networks, graph databases, modern ML frameworks, and cloud-based data platforms to build innovative data solutions Ensure adherence to best practices in data quality, model monitoring, version control, and reproducible analytics Lead and supervise a team of data scientists working on graph-related tasks Partner closely with Data Engineers, Software Engineers, Product Managers, and business stakeholders to translate business challenges into scalable Graph AI solutions. Main requirements: University degree in Mathematics, Physics, Computer Science, Engineering, Data Science, or a related quantitative field At least 6 years of experience in data science, machine learning and AI , including hands-on experience in designing, training and optimising Graph Neural Networks (GNNs) for production applications. Experience working with relational and non-relational databases Solid experience working with graph databases (e.g., Neo4j, Neptune) and proficiency in graph query languages (e.g., Cypher or Gremlin). Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly Strong programming skills in Python and experience with Pandas, NumPy , and similar data analysis libraries Strong analytical thinking, problem-solving ability, and attention to detail . Excellent communication skills and the ability to work collaboratively in a team environment Fluent in English Benefit from: Attractive remuneration package plus performance related reward Private health insurance Corporate pension fund Intellectually stimulating work environment Continuous personal development and international training opportunities The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Bring It to Life – Role-Specific Take-Home Task Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy Policy and the Confidentiality Undertaking.

Задачи: — Анализировать опоздания и "плохо построенные" маршруты. — Писать промышленный код и выводить его в продакшн. — Общаться с заказчиком, формализовывать требования. — Креативить, предлагать новые идеи. Требования: — Уверенное знание Python и стандартных DS библиотек. — Знание хотя бы одного диалекта SQL (предпочтительней PostgreSQL). — Знание основ ML и задач дискретной оптимизации. — Высшее образование в одной из сфер: математика, компьютерные науки.

Задачи: — разработка AI-решений для цифрового банкинга и персонализированных финансовых сервисов на облачной платформе — архитектура ML/AI и доставка моделей промышленного уровня — управление жизненным циклом моделей и практики MLOps — проектирование масштабируемых AI-платформ с поддержкой множества кейсов — обеспечение ответственного использования AI, управление моделями и рисками — взаимодействие с заинтересованными сторонами и стратегическое согласование Требования: — опыт в Data Science / AI не менее 5 лет, включая руководящий опыт — опыт в банковской сфере/финтехе (кредитный скоринг, борьба с мошенничеством, персонализация) — навыки управления жизненным циклом моделей и MLOps — уровень английского от Upper-Intermediate и выше Условия: — работа в проектах, связанных с цифровым банкингом и финансовыми сервисами — график работы: воскресенье–четверг (GMT+3) — локации: Грузия, Казахстан, Сербия, Молдова, Азербайджан, Беларусь

Location: Paris Workplace: OnSite ABOUT VOODOO Voodoo is a consumer tech company founded in Paris in 2013, with one mission: entertain the world. Today we are 1,000 people, generating $1b+ in annual revenue, profitably. Our games and apps have passed 7 billion downloads and reach 200 million+ active users every month, making Voodoo the #3 mobile publisher worldwide in downloads, after Google and Meta. We were backed by Goldman Sachs, Tencent and GBL along the way. TEAM Blitz is a gaming platform launched by Voodoo in 2021, allowing players to compete on mobile games for real cash prizes (head-up, tournaments, leagues, etc.). It is leveraging Voodoo's unique game portfolio to engage users in a fun and rewarding way. ROLE This role sits at the intersection of the Data and Gaming teams. You'll be the analytical partner to game designers and product managers, owning the measurement and tuning of the games themselves — from difficulty and game parameters to matchmaking fairness and the in-game economy. Your work directly shapes what players experience and how the games perform. MISSIONS: - Own the A/B testing cycle for games and game parameters — designing experiments, validating changes, and reading out results that drive core KPIs (engagement, RTP, rake, fairness, retention). - Analyze and calibrate game parameters — difficulty, scoring, completion rates, seed selection, and payout structures — to hit target player experience and economic goals. - Translate analyses into clear, actionable recommendations that shape game design and the product roadmap. - Build simulations and prototypes to pressure-test parameter and economy changes before rollout, then monitor them live once shipped. - Collaborate closely with game designers and engineers to embed data-driven decisions across the full game lifecycle. - Build and maintain dashboards and reports that keep the Gaming and Data teams aligned on critical game and economy metrics. PROFILE - 3+ years in analytical roles, ideally within gaming or a data-intensive product environment, comfortable working directly with product and design teams. - Skilled in SQL and Python; experience with large, complex datasets. - Strong grasp of A/B testing and statistical methods. - Comfortable with simulation and modeling to reason about game parameters, difficulty, and game economy outcomes. - Thrives in a fast-paced environment with rapid iteration. - Player-first mindset with genuine curiosity about games, player behavior, and game balance. BENEFITS - Competitive salary based on experience - Swile Lunch voucher - Gymlib (100% covered by Voodoo) - Premium healthcare coverage with SideCare, 100% covered for you and your family - Wellness activities in our Paris office - Remote days on Fridays

Location: Remote, California, United States, AMER From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role This is a unique role that sits at the intersection of economics, analytics, product, and strategy. You’ll combine rigorous quantitative analysis with customer research and commercial thinking to shape how Fivetran prices, packages, and monetizes its products. What You’ll Do Analyze product usage, deal, financial, and billing data to model pricing, packaging, and monetization scenarios. Design frameworks to assess willingness to pay, customer value, and price realization across customer segments and product lines. Conduct research on pricing strategies, packaging models, and monetization approaches across comparable and adjacent markets. Lead pricing and packaging strategy for new product launches, partnering with Product, GTM, and Finance to define commercial models Build value-based pricing and econometric models to quantify elasticity, customer ROI, and lifetime value. Design and execute pricing experiments Synthesize quantitative analysis, customer research, and competitive intelligence into executive recommendations that influence pricing strategy. Drive customer and prospect research to understand purchasing behavior, value perception, and pricing friction. Partner closely with Product, Analytics, Finance, Sales, Marketing, and Legal to deliver end-to-end pricing initiatives. Define KPIs and dashboards that measure pricing performance and identify optimization opportunities. Continuously evolve our pricing and packaging strategy to improve ARR growth, customer adoption, and value realization. Skills We’re Looking For 5–8 years designing or operating SaaS or sophisticated B2C pricing models, preferably with usage‑based or behavioral pricing experience Deep quantitative chops—an advanced degree (PhD/MSc) in Economics, Statistics, Operations Research, Applied Math, or similar Fluency in SQL and Python for large‑scale data analysis; proficiency with BI tools such as Looker or Tableau; bonus for dbt Hands‑on experience with conjoint, MaxDiff, Gabor-Granger, or Van Westendorp surveys and causal experiment design Strong attention to detail and data analysis skills – including interpreting results and recommending actions Proven record of turning complex models and analyses into recommendations and shipping changes that moved ARR, gross margin, or NRR Collaborative mindset with Product, Analytics, Finance, Sales, and Legal; you can navigate from whiteboard to contract terms with ease Strong communication and presentation skills with ability to influence at the executive level #LI-DJ1 #LI-Remote The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Pay Range $209,378 — $261,723 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: Limassol; Nicosia Workplace: hybrid The Role:  Are you passionate about transforming complex data into intelligent, business-driven solutions? Do you enjoy solving challenging problems, developing cutting-edge machine learning models, and collaborating with highly skilled professionals? We are looking for a Senior Data Scientist to join our growing Data Science team. In this role, you will play a key part in designing and delivering innovative data products that create measurable business impact. You'll work with large-scale datasets, advanced machine learning techniques, and modern technologies while collaborating with multiple teams, and business stakeholders to bring data-driven solutions into production. The main responsibilities of the position include: Lead the design, development, and delivery of high-impact data science and machine learning solutions. Translate complex business challenges into structured analytical approaches and scalable data products. Build, evaluate, and optimize advanced machine learning models, ensuring high standards of quality, performance, and reliability. Contribute to technical decisions and best practices across the data science lifecycle. Review and validate data preparation, feature engineering, model selection, experimentation, and documentation. Support the deployment and operationalization of machine learning models in batch and real-time environments. Present analytical insights and recommendations to technical and non-technical stakeholders. Ensure compliance with data quality, model governance, security, privacy, and responsible AI standards. Identify opportunities to leverage data science for automation, forecasting, personalization, optimization, and risk management. Collaborate closely with Data Engineers, Machine Learning Engineers, Software Engineers, Product Owners, and business stakeholders to develop production-ready solutions. Contribute to improving team processes, technical standards, and project delivery methodologies. Support the Lead Data Scientist in defining priorities, roadmaps, and strategic initiatives. Main requirements: University degree in Mathematics, Physics, Engineering, Computer Science, Data Science, or a related field. At least 5 years of experience in a similar role. Hands-on experience with Python libraries such as Pandas, NumPy, and Polars for data processing and analysis. Strong Python programming skills with the ability to write clean, maintainable, and production-ready code. Strong knowledge of modern machine learning techniques and advanced architectures, including Transformers and Graph Neural Networks (GNNs) . Experience with data visualization libraries such as Matplotlib, Seaborn, and Plotly . Good knowledge of SQL and statistical analysis. Excellent analytical thinking and problem-solving skills. High attention to detail and commitment to delivering high-quality solutions. Strong communication skills with the ability to explain technical concepts to non-technical audiences. Excellent verbal and written communication skills in English. A collaborative mindset, curiosity, and a passion for continuous learning. What would be considered as an advantage: Exposure to Natural Language Processing (NLP). Experience working with NoSQL databases. Knowledge of software engineering best practices. Experience working in Unix/Linux environments. Basic understanding of AWS services and cloud-based machine learning environments. Benefit from: Attractive remuneration package plus performance related reward Private health insurance Corporate pension fund Intellectually stimulating work environment Continuous personal development and international training opportunities The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Bring It to Life – Role-Specific Take-Home Task Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy Policy and the Confidentiality Undertaking.

Требования к кандидату: - Several years of experience as a Data Scientist - Strong Python skills - Strong SQL skills - Experience building production data products - Solid understanding of experimentation and statistics - Experience with modern data warehouses

Задачи: - написание сервисов для команды рекомендательных систем; - разработка систем мониторинга качества рекомендательных систем; - настройка мониторинга и алертинга качества данных; - написание unit тестов (pytest), тестов для различных участков ML пайплайна, участие в код ревью. Требования: - опыт работы с рекомендательными системами от 2х лет; - опыт полного цикла решения ML-задач: от аналитики до вывода моделей в прод (от 3-х лет); - отличные знания Python, SQL, классического ML-стека и соответствующих ему библиотек; - владение одним из DL фреймворков (torch/tensorflow/keras); - глубокое понимание рекомендательных систем: подходы, типичные проблемы, метрики, А\Б тестирование; - опыт написания Unit-тестов, разработки архитектуры и Code Review; - опыт работы с инструментами разработки и CI/CD — Git, Jenkins, GitLab, Jira.

Задачи: — Сбор, валидация и анализ данных из внутренних систем, разработка новых метрик и KPI. — Разработка ML-моделей для анализа временных рядов, прогнозирования сальдо счетов, LTV и оттока клиентов. — Кластеризация и сегментация базы, разработка моделей скоринга и расчет Life Time (LT). — Прогнозирование объема обращений и моделирование показателей эффективности (KPI) сервиса. — Формирование и проверка гипотез для улучшения ключевых бизнес-показателей на основе математических моделей. Требования: — Высшее образование в математике, финансах, экономике, информатике, физике, инженерии или аналогичных областях. — Исследовательский склад ума, творческий подход, настойчивость, инициативность, внимательность к деталям. — Критическое мышление и способность находить нестандартные подходы. — Уверенное владение инструментами BI аналитики, знание MySQL, Google Big Query, Python, Git. — Английский язык на уровне B2. Условия: — Работа в европейском офисе с отличным климатом. — Компенсация перелета и помощь с легализацией (релокационный пакет). — Конкурентная заработная плата, ДМС и пакет бенефитов. — Амбициозные задачи. — Работа в команде профессионалов в комфортабельном офисе в регионе с отличным климатом.

Responsibilities: • Conduct group sessions on AI, Data Science, ML models • Answer student questions and provide support The school teaches in Kazakh and is the first AI and Big Data school in Central Asia.

Responsibilities: • Conduct group sessions on AI, Data Science, ML models • Answer student questions and provide project feedback • Help find practical solutions beyond textbooks • Support students in their career transition • Participate in improving the curriculum Requirements: • Kazakh (C2) • three+ years experience in Data Science • Knowledge of mathematical statistics • Experience with regression and classification models • Familiarity with numpy, scikit-learn, pandas Optional requirements: • Experience in mentorship, teaching, or team leading • Experience in Computer Vision and RecSys projects • Participation in hackathons

Location: San Francisco, CA or Remote, US Our vision is to build the next generation platform to enable easy and fast creation of audio and video content powered by cutting-edge AI. Building a revolutionary way to record, transcribe, edit, and mix spoken audio and video comes with a series of unique challenges and requires solving hard and complex problems. As a lead product data scientist on the team, you will play a critical role in shaping our growth strategy, up-leveling our experimentation culture, and scaling our business. What You’ll Do Conduct in-depth analysis to shape product PLG motion and B2B strategy. Develop deep understanding of the product ecosystem and identify opportunities to drive activation, engagement, and monetization through actionable insights. Leveraging AI tools to build and maintain self-service analytics enabling stakeholders to access reliable metrics, size opportunities, design experiments, and interpret results independently. Improve execution rigor of product teams by owning success metrics and opportunity sizing. Brain buddy with product and engineering teams for day-to-day experiment design, deployment, and analysis. Provide creative solutions for tricky experimentation scenarios. Evolve experimentation culture and practices within the company. What You Bring 5–8 years of experience in a Data Scientist or similar role. 3+ years working in a growth function. Strong business and product intuition to identify opportunities in the growth ecosystem. Strong knowledge of statistical analysis and A/B tests. Strong SQL skills and proficient in at least one programming language such as Python or R. Excellent communication and collaboration skills. Curiosity, savviness to navigate in a dynamic environment, and a growth mindset. Having worked at a fast-growing start-up is a plus. The base salary range for this role is $200,000 - $250,000/year. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, level, and may vary from the amount above. About Descript Descript is building a simple, intuitive, fully-powered editing tool for video and audio — an editing tool built for the age of AI. We are a team of 150 and the backing of some of the world's greatest investors ( OpenAI , Andreessen Horowitz , Redpoint Ventures , Spark Capital ). Descript is the special company that's in possession of both product market fit and the raw materials (passionate user community, great product, large market) for growth, but is still early enough that each new employee has a measurable influence on the direction of the company. Benefits include a generous healthcare package, 401k matching program, catered lunches, and flexible vacation time. Our headquarters are located in the Mission District of San Francisco, CA. We're hiring for a mix of remote roles and hybrid roles.  For those who are remote, we have a handful of opportunities throughout the year for in person collaboration.  For our hybrid roles, we're flexible, and you're an adult—we don't expect or mandate that you're in the office every day. We do believe there are valuable and serendipitous moments of discovery and collaboration that come from working together in person. Descript is an equal opportunity workplace—we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We believe in actively building a team rich in diverse backgrounds, experiences, and opinions to better allow our employees, products, and community to thrive.

Требования: — Опыт работы в роли Data scientist от 2 лет; — Работа с одним из фреймворков PyTorch/TensorFlow; — Реализация и работа с RAG решениями; — Знание основных подходов для предобработки и векторизации текста; — Наличие опыта решения задач NLP для текста (Text Classification, NER, Text Summarization, QA); — Знакомство и понимание основных принципов современных SOTA моделей NLP; — Владение: git, docker, sql и одним из фреймворков для реализации api. Обязанности: — Работа с одним из фреймворков PyTorch/TensorFlow; — Реализация и работа с RAG решениями; — Знание основных подходов для предобработки и векторизации текста; — Наличие опыта решения задач NLP для текста (Text Classification, NER, Text Summarization, QA); — Знакомство и понимание основных принципов современных SOTA моделей NLP; — Владение: git, docker, sql и одним из фреймворков для реализации api.

Задачи: - Разработка ML-моделей на различных типах данных: табличные, графовые, NLP и событийные последовательности для прогнозирования отказов и сбоев в оборудовании; - Решение задач дискретной оптимизации; - Участие в исследовании новых источников данных и развитии feature store (в Apache Doris); - Поддержка полного цикла разработки DS/ML-продуктов - от идеи до продакшена; - Участие в создании и развитии AI-агента на базе LLM - от экспериментов до реального применения. Требования: - Опыт в роли Data Scientist от 1.5 лет; - Опыт end-to-end разработки ML-решений: от постановки задачи и работы с бизнесом до внедрения в production и поддержки моделей; - Отличное знание Python и глубокое понимание классических алгоритмов машинного обучения, опыт работы с NLP, временными рядами, задачами детекции аномалий; - Опыт работы с deep learning, включая RNN-like архитектуры и трансформеры; - Умение работать с БД (SQL), собирать и обрабатывать данные; - Уверенное понимание A/B-тестирования; - Высшее техническое образование.