Вакансии

• Опыт Data Scientist и в кредитных рисках (банки или финтех) с пониманием специфики.

Location: Remote; Remote - Brazil; Remote - EMEA Workplace: Remote ABOUT US Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we've built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We're passionate about maintaining this and work on the bleeding edge of AI to do so. Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco. We're a passionate team who love solving problems and want to make our customers' and coworkers' lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things. Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today. ABOUT THE ROLE We are hiring Senior Data Scientists across multiple teams at Constructor. Wherever you land, you will work with data from some of the world's largest ecommerce companies, applying statistics and machine learning to problems that directly move business metrics like revenue and conversion rate. Our data scientists design and analyze experiments, dig into how our ranking, personalization, and recommendation algorithms behave, and connect model performance to real business outcomes. During the interview process we will get to know your strengths and interests and match you with the team where you can have the biggest impact. WHAT YOU'LL DO - Design, run, and analyze A/B tests measuring impact on key business metrics like revenue, conversion rate, and profit - Apply statistical methods and machine learning to solve business and product problems - Develop a deep understanding of how our search, ranking, and personalization algorithms work, and how to evaluate and improve them - Analyze large-scale behavioral data to generate insights and recommendations for customers and internal teams - Build analyses, models, and tools that help teams make better decisions - Communicate findings clearly to technical and business stakeholders REQUIREMENTS - Strong experience solving business problems using data science and statistics - Solid knowledge of SQL and experience working with large datasets - Strong Python skills for analysis and modeling (pandas, NumPy, scikit-learn, visualization libraries) - Deep understanding of A/B testing, experiment design, and statistical inference PRODUCT & DATA UNDERSTANDING: - Understanding of machine learning systems: how models are trained, evaluated, and tuned - Experience connecting model or algorithm performance to product funnels and business metrics - Familiarity with ranking, recommendations, or search relevance is a plus COMMUNICATION & OWNERSHIP: - Ability to communicate insights clearly to both technical and business audiences - Comfortable working independently with multiple stakeholders in a fast-paced environment PREFERRED SKILLS: - Experience working in e-commerce or with large-scale user behavioral data - Experience in customer-facing analytical work BENEFITS - 🧠 Work with smart and empathetic people who will help you grow and make a meaningful impact. - 🎉 Regular team offsite events to connect and collaborate. - 🌎 Fully remote team - choose where you live. - 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year. - 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office. - 💻 Apple laptops provided for new employees. - 🧑‍🎓 Training and development budget for every employee, refreshed each year. - 👪 Maternity & Paternity leave for qualified employees. - 💵 Base salary: $80k–$120K USD depending on knowledge, skills, experience, and interview results - 📈 Stock options - offered in addition to the base salary 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: Remote - Brazil; Remote; Remote - EMEA Workplace: Remote ABOUT US Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we've built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We're passionate about maintaining this and work on the bleeding edge of AI to do so. Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco. We're a passionate team who love solving problems and want to make our customers' and coworkers' lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things. Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today. ABOUT THE ROLE We are hiring Senior Product Analysts across multiple teams at Constructor. Wherever you land, you will help product teams understand how their work translates into user behavior and business outcomes, and use data to shape where our products should evolve next. Our product analysts define the metrics that matter, build the connection between product performance and business results, and turn ambiguous questions into clear, actionable insights. During the interview process we will get to know your strengths and interests and match you with the team where you can have the biggest impact. WHAT YOU'LL DO - Define and validate the metrics that product teams use to measure success - Build metric frameworks connecting product and algorithm performance to business outcomes like revenue and conversion - Analyze user behavior and product funnels to identify opportunities and guide product strategy - Design, run, and analyze A/B tests to evaluate product changes - Set up analytics for product areas, from instrumentation to dashboards and reporting - Partner closely with product managers, engineers, and leadership to turn insights into decisions REQUIREMENTS - Strong track record of solving product and business problems using data - Solid knowledge of SQL and experience working with large datasets - Experience with Python for data analysis (pandas, NumPy, visualization libraries) - Deep understanding of A/B testing and statistical concepts PRODUCT & DATA UNDERSTANDING: - Experience defining metrics, building metric trees, and analyzing product funnels - Ability to connect product changes to business outcomes and communicate the "so what" - Familiarity with ML-driven or AI products is a plus Communication & ownership: - Proven ability to work independently and own an analytics area end to end - Ability to communicate insights clearly and influence product strategy - Comfortable bringing structure to ambiguous questions in a fast-paced environment Preferred skills: - Experience working in e-commerce - Experience being the first or primary analyst embedded in a product team BENEFITS - 🧠 Work with smart and empathetic people who will help you grow and make a meaningful impact. - 🎉 Regular team offsite events to connect and collaborate. - 🌎 Fully remote team - choose where you live. - 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year. - 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office. - 💻 Apple laptops provided for new employees. - 🧑‍🎓 Training and development budget for every employee, refreshed each year. - 👪 Maternity & Paternity leave for qualified employees. - 💵 Base salary: $80k–$120K USD depending on knowledge, skills, experience, and interview results - 📈 Stock options - offered in addition to the base salary 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: Remote - Brazil; Remote - AMER; Remote - EMEA Workplace: Remote ABOUT US Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we’ve built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We’re passionate about maintaining this and work on the bleeding edge of AI to do so. Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco. We’re a passionate team who love solving problems and want to make our customers’ and coworkers’ lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things. Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today. ABOUT THE ROLE We are hiring Data Analysts to work across multiple teams at Constructor, including Data Science Integrations, Ranking, Recommendations, AI Shopping Agents, Offsite Search Optimisation, Personalization and Retail Media. In this role, you will work at the intersection of data, product, and machine learning. You will analyze user behavior, design and evaluate experiments, define metrics, and generate insights that directly influence product decisions and business outcomes. You will collaborate closely with engineers, data scientists, product managers, and business stakeholders, helping translate data into actionable improvements across our platform. WHAT YOU WILL DO - Analyze user behavior and large-scale datasets to identify patterns, issues, and opportunities for improvement - Design, run, and analyze A/B tests to evaluate product changes and measure impact on key business metrics - Define and validate metrics that reflect both user experience and business outcomes - Build dashboards, reports, and data tools to support decision-making across teams - Partner with customers, engineering, product, and business teams to translate insights into product improvements - Work with SQL, Python, and distributed data systems to process and analyze large volumes of data REQUIREMENTS We are looking for strong analytical thinkers who are comfortable working with data to drive product and business decisions. Core skills: - Strong analytical skills and experience solving business problems using data - Solid knowledge of SQL and experience working with large datasets - Experience with Python for data analysis (pandas, NumPy, visualization libraries) - Understanding of A/B testing and statistical concepts Product & data understanding: - Understanding of machine learning pipelines, training data quality, and model evaluation - Familiarity with ranking, recommendations, or search relevance is a plus - Experience defining metrics, building metric trees, and analyzing product funnels Communication & ownership: - Ability to communicate insights clearly and translate business needs into analytical solutions - Comfortable working with multiple stakeholders in a fast-paced environment Preferred Skills: - Experience in a customer-facing role - Experience working in e-commerce or product analytics BENEFITS - 🧠 Work with smart and empathetic people who will help you grow and make a meaningful impact. - 🎉 Regular team offsite events to connect and collaborate. - 🌎 Fully remote team - choose where you live. - 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year. - 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office. - 💻 Apple laptops provided for new employees. - 🧑‍🎓 Training and development budget for every employee, refreshed each year. - 👪 Maternity & Paternity leave for qualified employees. - 💵 Base salary: $80k–$120K USD, depending on knowledge, skills, experience, and interview results - 📈 Stock options - offered in addition to the base salary 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: Гибрид, Удаленно, Офис Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Обязанности анализ данных и проверка гипотез для решения бизнес-задач; разработка и валидация ML-моделей (регрессия, классификация, кластеризация, ансамбли) feature engineering: подготовка и проектирование признаков; построение интерпретируемых моделей и explanation-инструментов (XAI); подготовка прототипов моделей и передача их в пилотирование / промышленную эксплуатацию; визуализация результатов, подготовка презентаций и консультирование заказчика. Требования опыт от 5 лет на позиции Data Scientist / аналитика данных; уверенный Python (scikit-learn, pandas, numpy), SQL, опыт с PostgreSQL и ClickHouse; понимание валидации моделей и борьбы с переобучением; навыки визуализации данных и подготовки презентаций; математическое моделирование, статистика, системный анализ. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.

Location: Kyiv; Lviv Workplace: onsite Ajax Systems — міжнародна технологічна компанія і найбільший у Європі виробник охоронних систем. Ми шукаємо фахівця до Operations підрозділу на позицію Data Analyst. Необхідні знання та навички: SQL та робота з даними: SQL (JOIN, CTE, Window Functions), Databricks / Spark SQL, Delta Lake, моделювання та перевірка якості даних. Автоматизація: Google Sheets (QUERY, ARRAYFORMULA, IMPORTRANGE), Apps Script, API. Інструменти: Jira (JQL, REST API), Confluence, BI-дашборди. Виробничі процеси: розуміння BOM, NPI, специфікацій, 1С / SAP MM, планування матеріалів і закупівель. Аналітичні навички: робота з великими обсягами даних, визначення KPI, виявлення помилок і пошук першопричин. Системне мислення, уважність до деталей, проактивність, самостійність та комунікація. Буде плюсом: Досвід роботи з Python (pandas, numpy), ETL-процесами та автоматизацією звітності. Знання інструментів оркестрації: Airflow, Databricks Jobs. Досвід роботи з dbt, Unity Catalog, Data Lineage та Data Catalog. Розуміння процесів планування закупівель, ABC/XYZ-аналізу, Lead Time та прогнозування запасів. Досвід інтеграції систем через API та Webhooks, створення ботів для Jira. Досвід роботи з великими наборами даних (CSV / Parquet, 10+ млн рядків). Навички побудови прогнозних моделей і статистичного аналізу. Розуміння BPMN, User Stories, Git. Завдання: Збирати, обробляти та звіряти дані з різних джерел (РНД-план, 1С, Jira тощо). Розробляти та підтримувати аналітичні моделі, звіти й BI-дашборди. Автоматизувати збір, обробку даних і регулярну звітність. Аналізувати виробничі процеси, потреби в матеріалах, запаси та закупівлі. Виявляти помилки, розбіжності й операційні ризики, знаходити їхні причини та пропонувати рішення. Розробляти метрики й KPI для моніторингу ефективності R&D Operations. Інтегрувати внутрішні системи та автоматизувати обмін даними між ними. Взаємодіяти з R&D, виробництвом, закупівлями та плануванням для оптимізації процесів. Пропонуємо: Можливість пропонувати та реалізовувати власні ідеї, які впливають на продукт та його масове виробництво; Місце у стрімко зростаючій компанії з вмотивованою професійною командою; Конкурентну заробітну плату; Медичне страхування; Корпоративні заняття з англійської мови; Можливість взяти участь у внутрішньому проєкті бета-тестування систем безпеки Ajax; Знижки на продукти компанії та партнерів Ajax Systems — це українська історія успіху, яка виросла в глобальний продукт. Пристроям Ajax довіряють уже понад 4,5 мільйони кінцевих користувачів і 330 тисяч PRO-користувачів у більш ніж 180 країнах. Компанія пропонує комплексні рішення для захисту житлових і комерційних об'єктів різного масштабу. Нині портфоліо Ajax налічує 280 пристроїв для захисту від вторгнення, відеоспостереження, пожежної безпеки та комфорту й автоматизації.

ML / DS Engineer (Classic ML) IT Вакансии Мы ищем опытного ML/DS инженера для разработки и внедрения моделей классического машинного обучения, решения бизнес-задач и построения ML-пайплайнов.

Формировать позиционирование сервисов работы с данными: определение основных сценариев использования, конкурентный анализ и проработка стратегия вывода на рынок отдельных решений. Представлять возможности наших платформ на внешних и внутренних мероприятиях.

Исследовать поведение пользователей и искать точки роста продукта на данных: например, как фото, описания, доступность номеров влияют на конверсию и бронирования; Оценивать потенциальный эффект продуктовых инициатив и готовить рекомендации, которые помогают команде решить, что делать в первую очередь;

Сегодня мы расширяем команду и ищем Инженера данных для работы над внешними проектами в таких сферах, как ритейл, EdTech, банкинг и других. Чем предстоит заниматься Проектировать и разрабатывать потоки данных на ETL/ELT-инструментах;

Location: Москва Workplace: Гибрид, Офис Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Обязанности ​​​​​​ анализ данных и проверка гипотез для решения бизнес-задач; разработка и валидация ML-моделей (регрессия, классификация, кластеризация, ансамбли) feature engineering: подготовка и проектирование признаков; построение интерпретируемых моделей и explanation-инструментов (XAI); подготовка прототипов моделей и передача их в пилотирование / промышленную эксплуатацию; визуализация результатов, подготовка презентаций и консультирование заказчика. Требования опыт от 2 лет на позиции Data Scientist / аналитика данных; уверенный Python (scikit-learn, pandas, numpy), SQL, опыт с PostgreSQL и ClickHouse; понимание валидации моделей и борьбы с переобучением; навыки визуализации данных и подготовки презентаций; математическое моделирование, статистика, системный анализ. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.

Location: Москва Ищем специалиста, который сочетает инженерный подход к разработке ETL-процессов с глубоким пониманием аналитики данных. Обязанности Чем предстоит заниматься: • проектирование на основе спецификаций (Spec-driven) • разработка ETL/ELT процессов • оркестрация и мониторинг • аналитическая поддержка • работа с документацией • взаимодействие со стейкхолдерам Требования Мы ждём что ты: • Опыт работы от 4 лет в ролях Data Engineer, DWH-разработчика или системного аналитика данных • Продвинутый уровень SQL: оконные функции (ROW\_NUMBER, LAG/LEAD), CTE, понимание плана выполнения запроса (EXPLAIN) и оптимизации • Уверенное владение Apache Spark: опыт промышленной разработки на языке Scala, опыт работы с экосистемой Big Data: HDFS, Hive Metastore, YARN, Parquet/ORC форматы • Практический опыт работы с оркестраторами (Airflow, Luigi или аналоги) • Владение Git: ветвление (GitFlow), код-ревью, разрешение конфликтов Будет плюсом: • Опыт проектирования витрин с нуля под требования конкретных продуктовых метрик • Python (Pandas, PySpark) для вспомогательных скриптов, тестирования или легкого анализа • Начальные знания и интерес к развитию в области Machine Learning и Data Analysis Условия Что мы предлагаем: • офисный формат работы • ежегодный пересмотр зарплаты, годовая премия • 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 • подписку Прайм с возможностью совместного использования на троих членов семьи • вознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Мы ищем целеустремленного и амбициозного Data Scientist, который готов развиваться в области AI, ML и Финансов. Мы отвечаем за задачи по AI-трансформации, связанные с Блоком Финансы, нашим основным заказчиком является Казначейство Сбера. Нашей задачей является внедрение AI и ML в таких процессах, как продуктовое ценообразование на портфельном и индивидуальном уровне, установление единых трансфертных ставок, бизнес-планирование, с целью улучшения финансовых показателей банка. В нашу работу входит анализ данных, построение моделей, внедрение их в процесс, общение с заказчиками, представление результатов руководству Банка. В работе используем как стандартные модели и алгоритмы, так и тестируем более продвинутые методы, в том числе, совместно с Лабораторией искусственного интеллекта Сбера. Обязанности * Разработка ML-моделей и алгоритмов * Вывод в production ML-моделей и расчетных модулей * Аналитика на больших данных * Поддержка реализованных решений * Разработка ML-моделей и алгоритмов для прогнозирования временных рядов Требования * продвинутые знания в области математики (мат.анализ, линейная алгебра, теория вероятностей, мат.статистика) * python: типы данных, структуры, ООП * классический ML: задачи (классификация, регрессия), метрики, basic ML stack (pandas, numpy, sklearn, catboost, xgboost), SQL * BigData stack (Hadoop, Spark, SparkML) * умение работать с git, Jira, Confluence. Будет плюсом: * знания в области финансов * опыт продуктовой аналитики * опыт работы с временными рядами (анализ, разработка моделей) * опыт работы с LLM (langchain, langgraph) * опыт end-2-end разработки ML-моделей (EDA-MVP-Solution-Validation-Production) * опыт backend разработки. Условия * комфортный современный офис рядом с м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * 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 * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

​​​​​​ анализ данных и проверка гипотез для решения бизнес-задач; разработка и валидация ML-моделей (регрессия, классификация, кластеризация, ансамбли) feature engineering: подготовка и проектирование признаков;

Location: Armenia; Georgia; Uzbekistan; Egypt We’re looking for a Data Analyst to work on our loyalty and retention mechanics. You’ll tell the team whether a mechanic actually drives more bookings, what it costs, and how to tune it. The work goes well beyond reporting. You’ll segment partners by behavior, run and read experiments, build financial models for new program features, and turn your findings into rules that the Retention, Commercial and Finance teams act on. Requirements 2-4 years as a data or marketing/product analyst, ideally in e-commerce, travel, fintech or a marketplace. Explains findings clearly to non-technical people and turns ambiguous questions into a structured plan. English level B2+ (written and spoken). Strong SQL: window functions, CTEs, query optimization. Experience with Vertica, Trino, PostgreSQL or similar. Solid A/B testing: experiment design, power and significance, choosing the unit of randomization, calculating and interpreting results. Experience with a BI tool: we use Tableau (Looker or Power BI experience is fine too). Can work with large, messy data where business logic hides in free-text fields and edge cases. Hands-on experience with Claude Code or similar agentic coding tools (Cursor, Copilot, etc.): writing effective prompts, working with agents, and maintaining project context files (such as CLAUDE.md) so results are repeatable. Comfort building financial or scenario models in spreadsheets, with clear assumptions and adjustable parameters. Proactive approach: you spot inefficiencies in reporting and analysis workflows and fix them yourself (automation, reusable queries, templates), rather than waiting to be asked. Nice to have Hands-on experience with loyalty, CRM, rewards or affiliate program analytics: points economics, liability, redemption and breakage. Experience with segmentation and cohort or retention analysis. Python for analysis (pandas, scipy, seaborn). Experience with dbt and Airflow. Methods beyond classic A/B tests (causal inference, diff-in-diff). Benefits Flexible schedules and opportunity to work remotely. Ambitious and supportive team who love what they do, appreciate each other, and grow together. A structured onboarding, a personal development plan, and regular internal lectures and demos from the team. Internal programs for adaptation and training, development of soft skills, and leadership abilities. Partial compensation for participating in external training and conferences. Corporate English school: Group and individual lessons, speaking clubs with colleagues from all over the world. Corporate prices on hotels and travel services. MyTime Day Off - an extra non-working day without loss of compensation.

- Build simulation frameworks to stress test onchain strategies under adverse conditions: depegs, oracle failures, liquidity crunches, cascading liquidations. - Model concentration risk, counterparty exposure, and correlation dynamics across the portfolio.

Location: Intellias Meet your recruiter Khrystyna Derpak khrystyna.derpak@intellias.com https://www.linkedin.com... Vacancy details AI/ML Engineering Data Scientist Senior Bulgaria, Croatia, Poland, Portugal, Spain Remote APPLY NOW REFER A FRIEND Let’s breathe life into great tech ideas! With 3,000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world. What project we have for you Join a transformative data and AI platform initiative aimed at modernizing enterprise-scale capabilities and enabling real-time decision-making. This project delivers a comprehensive roadmap covering AI, MLOps, data governance, and platform scalability, supporting a shift towards data-first operations and intelligent automation. What you will do Platform setup. With customer’s platform team, provision and configure the Databricks environment in customer’s cloud account: catalog and permissions, compute (including GPU), secrets, experiment tracking. Secure data ingestion. Build repeatable ingestion of raw verification outputs and document images: parsing, pseudonymisation, data-quality checks, schema handling. Feature engineering at scale. Implement the feature tables: batch image-embedding jobs; exact and approximate linkage keys; cross-transaction and velocity aggregates; pseudonymous entity resolution. Modelling support. Implement feature-selection and mixed-data clustering methods. Run model comparisons and stability tests, and support density-model training runs. Automation. Orchestrate the end-to-end pipeline as a scheduled, idempotent, re-runnable workflow. Monitoring. Set up the data-quality and drift-monitoring prototype, with alerting, on feature and score tables. Privacy engineering. Implement access controls, provenance fields, lineage and the scripted deletion procedure. Confirm that no raw personal data reaches the analytic layer. Documentation and handover. Write runbooks and give a live walkthrough, so engineers can operate everything independently What you need for this PySpark & Spark SQL: Nested-JSON flattening (explode, structs),`mapInPandas` / pandas UDFs, window functions for velocity and distinct-count aggregates, partitioning and performance tuning Databricks: Unity Catalog (catalogs, schemas, grants, column masks, tags, lineage), external locations on S3, cluster / compute policies incl. GPU, Auto Loader, Delta (MERGE, time travel, VACUUM), Workflows, Repos, secret scopes AWS: S3, IAM roles / instance profiles, KMS decryption in jobs, Secrets Manager, basic cost awareness Data engineering for ML: Medallion design (Bronze / Silver / Gold), schema evolution, idempotent loads, DQ profiling, Feature Engineering in UC (feature tables) Pseudonymisation in pipelines: HMAC tokenization with per-key-type keys, normalisation (Unicode NFKD, case, token sort), phonetic keys, never logging raw values, scripted deletion (DROP / VACUUM / secret destruction) Entity resolution (implementation): Blocking / candidate generation with exact and approximate keys, edit-distance tolerance, match scores, surrogate IDs, conflict counting rather than merging Image processing at scale: Running a GPU batch job that decrypts, crops and embeds images in memory (PyTorch / timm), PCA, LSH bucketing Mixed-data clustering: Hands-on: `kmodes` (k-prototypes), `gower` + `kmedoids` with sampling, R `kamila` on Databricks, `StepMix` (latent class), bootstrap ARI Bayesian statistical analysis: Hands-on experience applying Bayesian methods to real-world data problems, including prior/posterior modelling, Bayesian inference, uncertainty estimation, and interpretation of probabilistic results. Feature selection: Mutual information, correlation pruning, PCA. Can run a BPSO / GA search with`mealpy` MLOps & monitoring: M*Lflow experiments and registry (aliases), Lakehouse Monitoring * (profile and drift metrics on Delta tables), SQL alerts, PSI / JS divergence Handover: Writes runbooks and README-level documentation. Leaves a single end-to-end Workflow that someone else can run Nice to have Experience with AssureID / identity-verification JSON outputs. PyOD and basic PyTorch training (to support A on the VAEs in week 2). 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 AWS Python

Location: Paris; Amsterdam; London; Lausanne Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE Mistral AI is seeking Applied Scientists and Research Engineers focused on tabular data. You will design, train, and deploy SOTA models that understand, query, and reason over structured data, and apply them to diverse use cases. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry. WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. - Generate and curate datasets of tables, spreadsheets and databases, and build evaluators and benchmarks for table understanding, text-to-SQL, and prediction on tabular data. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. ABOUT YOU - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Experience training or fine-tuning large language models, or tabular foundation models (e.g. TabPFN). - Strong background in machine learning on tabular data, including classical baselines (e.g. gradient boosting), and comfortable with SQL, pandas, and messy real-world data. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - Ex-founder or builder - PhD / Master in a relevant field (Computer Science, Statistics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Experience with text-to-SQL, table question answering, or spreadsheet agents. - Experience with reinforcement learning using verifiable rewards (e.g. query execution). - Experience working on large code bases or large machine learning models at scale. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.