Данные и ML вакансии - гибрид

Location: Warsaw, Mazowieckie, Poland; Sofia City, Bulgaria; Limassol, Cyprus Workplace: hybrid We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team. As a Data Engineer , you will play a crucial role in our data team, contributing to developing and maintaining data pipelines and systems. You will work closely with data scientists, analysts, and other stakeholders to ensure the availability and reliability of data for decision-making and analytics. Your responsibilities will encompass data ingestion, transformation, and delivery, as well as maintaining and optimizing data infrastructure. The Data Engineer is expected to contribute to developing and maintaining data infrastructure, ensuring data reliability and availability. You should be able to work independently and as part of a team, adapting to changing data needs and collaborating with data professionals to provide valuable insights to the organization. Staying current with data engineering best practices and emerging technologies is essential for success in this role. Responsibilities: Design, develop, and maintain data pipelines that ingest process, and deliver data from various sources, ensuring data quality and reliability. Data Modeling: Create and maintain data models to support reporting, analytics, and business intelligence needs, optimizing data structures for performance and efficiency. Implement ETL processes to transform raw data into meaningful insights, handling data transformation, aggregation, and enrichment. Monitor and address data quality issues, implement data validation processes, and establish data governance practices. Manage and optimize data storage, processing, and distribution systems, ensuring scalability and performance. Collaborate with data scientists, analysts, and cross-functional teams to understand data requirements and deliver solutions that meet business needs. Document data engineering processes, pipelines, and systems to maintain clear and accessible knowledge for team members. Requirements: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field. Minimum of 3 years of experience in data engineering or a related field. Proven experience with Redshift and Snowflake. Experience with DBT. Experience with Apache Airflow for workflow orchestration. Proficiency in Python for data pipeline development and scripting. Experience with AWS cloud services, including S3, EC2, and EMR. Familiarity with Kafka for real-time data streaming. Familiarity with data visualization and reporting tools (e.g. Tableau, Power BI or Looker). Project management skills using Jira or similar tools. Ability to collaborate effectively with cross-functional teams and understand business data needs. Strong problem-solving skills, a proactive approach to troubleshooting data issues, and critical thinking abilities. Adaptable and open to learning new technologies and methodologies. What you will get in return: • Competitive Salary: We believe great work deserves great pay! Your skills and talents will be rewarded with a salary that makes you feel valued and motivated. • Work-Life Harmony: Join a company that genuinely cares about you - because your life outside of work matters just as much as your time on the clock. #LI-Hybrid • Generous Time Off: Need a breather? Our annual leave policy lets you recharge and enjoy life outside of work without a worry. • Employee Referral Program: Love working here? Share the love! Bring your talented friends on board and get rewarded for growing our awesome team. • Comprehensive Health & Pension Benefits: From medical insurance to pension plans, we’ve got your back. Plus, location-specific benefits and perks! • Workation Wonderland: Live your digital nomad dreams with 30 extra days to work remotely from anywhere in the world (some restrictions apply). Adventure awaits! • Volunteer Days: Make a difference! Take two additional paid days each year to support causes you care about and give back to the community. Be a key player at the forefront of the digital assets movement, propelling your career to new heights! Join a dynamic and rapidly expanding company that values and rewards talent, initiative, and creativity. Work alongside one of the most brilliant teams in the industry.

— Развитие моделей поискового ранжирования и рекомендательных систем. — Тюнинг моделей и feature engineering.

онлайн-интенсив 1 месяц; вы изучаете теорию и отрабатываете ее с помощью практических заданий;

Help migrate an existing SAP BW data warehouse to Snowflake, rebuilding transformations with SQL and dbt while preserving business logic. Hands-on DWH transformation and migration experience.

⁃ Развивать Data Lakehouse и единое DWH. ⁃ Строить ETL/ELT-пайплайны от источника до готовой витрины.

исследование клиентского опыта в рамках процессов оздоровления и взыскания, поиск «узких» мест в процессах и использование передовых инструментов для проведения локальных исследований (графовый анализ, LLM для поиска инсайтов, самовоспроизводящиеся ИИ-решения, disrupt-проекты). создание ИИ-решений, влияющих на клиентский опыт.

строить/улучшать модели для разных частей всего пайплайна. заниматься полным циклом DS/ML задач.

🕹 Список обязанностей: Разрабатывать Python / SQL-пайплайны загрузки и обработки данных из файлов, API и информационных систем. Проектировать таблицы хранилища: сущности, связи, правила преобразования.

Компания Aston приглашает на позицию Дата инженер (ученик) с последующим трудоустройством. Задачи: — пройти онлайн-интенсив длительностью 1 месяц, изучая теорию и выполняя практические задания; — совмещать обучение с работой; — после успешного окончания интенсива зачисление на стажировку в Лабораторию ASTON; — обучение на стажировке 3-4 месяца, 5 дней в неделю с 9:00 до 18:00 с перерывом на обед; — изучение теории с еженедельными проверками; — практика на учебных проектах под руководством опытного технического руководителя; — подготовка к собеседованию и самопрезентации; — посещение офиса обязательно для кандидатов, где есть офис компании; — для кандидатов из городов без офиса обучение возможно удаленно; — после старта на коммерческом проекте формат работы гибридный (3 дня в офисе ASTON, 2 дня удаленно) до уровня М2, затем полное посещение офиса заказчика; — возможны командировки в Санкт-Петербург или Москву. Требования: — законченное высшее или среднее специальное профильное образование; — готовность пройти стажировку в компании ASTON. Условия: — выплата стипендии во время обучения; — официальное трудоустройство; — доступ к корпоративной программе обучения; — регулярный пересмотр и повышение зарплаты после выхода на проект; — гарантированный финансовый бонус при старте на коммерческом проекте; — офис в центре города, корпоративные мероприятия, частичная компенсация спортивных абонементов. Требуемые навыки: визуализация, математическая статистика, NoSQL, Apache Hadoop, Greenplum, базы данных, Agile, Python, SQL.

Предстоит: Работать с профессиональными базами данных и хранилищами данных, разрабатывать и оптимизировать SQL-запросы; Использовать Python для анализа данных, автоматизации процессов и решения прикладных задач;

разработка классических LLM агентов. разработка tools для агентов, а также skills-инструкций для LLM.

Задачи: — работать с большими данными в экосистеме Hadoop (PySpark, SQL) — от выгрузки и разведки до построения витрин для моделей — разрабатывать индивидуальные модели эластичности и клиентского поведения в сегменте B2C — от прототипа до продвинутого пайплайна обучения и предсказаний — проверять бизнес-гипотезы и превращать их в измеримый эффект: дизайн и оценка A/B-тестов (мэтчинг, продвинутые методы causal inference, интерпретация результатов) — выстраивать коммуникацию с заказчиками: согласовывать метрики, защищать подходы, показывать ценность данных на понятном языке — обеспечивать надёжность и мониторинг внедрённых решений — чтобы модель работала стабильно и приносила пользу каждый день. Требования: — опыт работы Data Scientist от 2х лет — техническое образование (будет плюсом если выпускник - МГУ, МФТИ, ВШЭ и других ведущих вузов страны) — понимание теории вероятностей и статистики — уверенное владение широким спектром ML-алгоритмов — регрессия, классификация, кластеризация, а также uplift-моделирование (способность оценивать причинно-следственные эффекты, а не просто предсказывать) — владение Python и ML библиотеками (numpy, sklearn, pandas, matplotlib/seaborn/plotly, catboost/lightgbm/xgboost, etc.) — плюсом будет опыт работы с pytorch, pyspark Условия: — комфортный современный офис рядом с м. Кутузовская — возможность выбрать удобный график – офис/гибрид — ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования) — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте (для вакансий уровня Junior) — 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.

• Искать точки роста. Разбираться, где и почему сценарий работает недостаточно хорошо.

Location: Paris, France Workplace: Hybrid HEALTH CAN’T WAIT. Not for symptoms to get worse. Not for a six‑month appointment. Not for a system to catch up. But that’s exactly how healthcare works today. You wait, until you can’t. Alan exists to end the wait. Health is a universal right, and we believe this right can only become real when it’s coupled with prevention. We need to stop treating health as something we repair and start treating it as something we build, every day. It’s not solely a question of willpower. It’s the healthcare system itself that needs to work for everyone, in a sustainable way. So we are building the new standard in prevention insurance. Alan is the first company that integrates insurance, prevention, and care into a single, acclaimed user experience. We are on an incredible journey to build a global leading company, with a unique culture https://alan.com/en/careers. We already partner with 40K+ companies of all sizes, serving more than 1M+ members, and have reached €800M+ in ARR. Prevention as the new norm. That's what we're building with our team of 1000+ people. If it speaks to you: we're hiring across France, Spain, Belgium, and Canada. And beyond. ⭐️ THE DATA FOUNDATIONS TEAM ⭐ At Alan, every decision we make about our members' care, contracts and claims is a data decision. The Data Foundations team builds the platform that makes those decisions possible in a safe way. - Being part of the Data Foundations team means you’ll build, maintain, and improve the Data Platform used by everyone at Alan. - We enable Alan’s data-driven nature and help our colleagues make the most of their data. - Partner closely with people across Alan (technical and non-technical) to understand their needs and build data solutions they can trust and use effectively. - We own and manage all data-related tools that power Alan. - AI is changing the way companies work with data: agents are becoming first-class users of our data warehouse. It opens a world of new usage and exciting features, as well as concerns around security, data quality and governance. We are building the foundations that allow Alan to make the most of this exciting new paradigm. - Alan is expanding quickly: we went from 4 to 6 countries this year and we won’t stop there. Our objective is to onboard new countries in weeks, not months. Having strong data foundations is a cornerstone of that expansion, allowing our teams to make sense of a patchwork of insurance systems, regulations and reporting rules. - Examples of our missions: - improve the developer experience when building and maintaining data pipelines, - enable reliable and secure access to our data warehouse for Alaners and AI agents, - strengthen security and governance around our data assets, - define and implement standard data practices across Alan, - maintain and evolve our core data infrastructure to accommodate Alan's international expansion and growing product breadth… - Our core tools include Python, Airflow, Snowflake, AWS/GCP, Metabase, Terraform, dbt, and others. - Who you'll work with: Data Foundations is a small, high-leverage team inside the Tech Foundations area, whose mission is to enable product crews through world-class infrastructure, developer experience, operational excellence, and built-in security. You'd be joining as one of its core engineers, working daily with the whole Data community at Alan. 🎯 EXPECTED SKILLS AND ABILITIES You would thrive at Alan if most of this sounds like you: - Passionate about owning ambitious problems and developing simple solutions for them. - 3+ years of experience demonstrating impact in Data positions. We welcome candidates from early-career to highly experienced profiles. You may already have strong expertise in Data Engineering, or be an experienced data or software engineer looking to deepen your specialization in this area. - Experience building and operating production data infrastructure: orchestration (Airflow or similar), a cloud data warehouse, infrastructure as code. - Experience designing systems, tools or libraries used by other engineers, scientists or analysts. - Proficient in Python and SQL. Setting a high standard of rigor and precision for yourself, interested in your craft. - Curious about AI and eager to use it thoughtfully to increase your impact. - Great listening and communication skills. - Humble, kind, collaborative, and still willing to grow (no matter your seniority!). - Fluent and clear in English, both oral and written (no need to speak French!). For this role, we are looking to hire within the C0-E level range https://alan.com/en/careers/a/salary-equity. ⚙️ IMPORTANT NOTE: WE HIRE PEOPLE, NOT ROLES. If you're excited about this opportunity but don't check every box, we'd love to hear from you. Everyone, no matter how underrepresented, should feel free to apply, as it can only bring learning or success. If you identify yourself as a woman: Did you know that research shows women often apply only when meeting 100% of requirements? Remember, this is just a guide, not a checklist. We'll be thrilled to receive your application! 🔖 Check out our About Alan https://alan.com/about and Career https://alan.com/careers pages, as well as our Medium https://medium.com/alan, blog https://blog.alan.com/ and Glassdoor page https://www.glassdoor.com/Overview/Working-at-Alan-EI_IE1696043.11,15.htm for more info. YOU WANT TO KNOW MORE ABOUT ALAN? - 🙌 Perks & Benefits https://alan.com/en/careers/a/salary-equity: Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers. - 🤘 A strong culture https://alan.com/en/about/a/leadership-principles: People joining Alan are often surprised and delighted by our innovative working method. We have a set of cultural values that guide our approach to work 🔄 A quick note about the process Note: While you're applying for a specific area, you may join a different engineering team based on where we think you'll have the most impact. Check out descriptions of other areas here https://www.notion.so/Software-Engineering-Areas-Alan-2c61426e8be7805bacd2cdbc08c32640?pvs=21. #LI-DNP

💎 Создание и развитие собственных базовых языковых моделей Авито: проверка гипотез в области претрейна, continual pre-training, post-training, RL и синтетических данных, масштабирование обучения и оптимизация инференса (квантование, speculative decoding), построение процедур оценки качества моделей, написание продакшен-кода на Python и PyTorch.

Стек: Python, SQL, Spark, PyTorch, ClickHouse, Redis, S3.

разработка PoC и MVP AI-агентов с использованием фреймворков для работы с LLM. адаптация и дообучение LLM на внутренних и внешних данных (SFT, LoRA, DPO, GRPO).