Middle Data Scientist (ML Engineer)

X-FLOW is a mobile game development company established in 2018. We gained recognition after the release of Happy Color, the most popular digital coloring book and one of the most successful ad-driven mobile apps in the world. We take pride in our diverse and talented team and partners, spread across the UK, Cyprus, the Netherlands, and other regions worldwide.

We are looking for an experienced Lead Data Scientist to drive the development of machine learning solutions for advertising monetization and personalization, while providing technical leadership and mentoring to the Data Science team.

In this role, your primary focus will be optimizing advertising revenue through ML-driven decision making, while also evolving recommendation systems and user personalization that improve engagement and long-term product value. You will work closely with Product, Engineering, Analytics, and Ad Monetization teams, while mentoring and leading other Data Scientists.

Responsibilities:

• Lead Data Science initiatives focused on advertising monetization, maximizing revenue while maintaining a great user experience.
• Develop ML models for ad targeting, ranking, pricing, revenue prediction, and monetization optimization.
• Improve recommendation and personalization systems to increase user engagement, retention, and lifetime value.
• Analyze user behavior and advertising performance to identify growth opportunities and drive product decisions.
• Design, analyze, and interpret A/B tests and other experiments.
• Collaborate closely with Product Managers, Engineers, and Analysts to define roadmap and prioritize high-impact initiatives.
• Mentor Data Scientists through technical guidance, code reviews, and best practices.
• Drive the adoption of scalable ML solutions and ensure high standards for experimentation and model quality.
• Present insights and technical solutions clearly to both technical and non-technical stakeholders.

Requirements:

• 5+ years of experience in Data Science, preferably in consumer mobile products.
• Proven experience with advertising monetization, revenue optimization, or advertising analytics.
• Strong experience building recommendation, personalization, or ranking systems.
• Advanced proficiency in Python and SQL.
• Hands-on experience with machine learning models, including classification, regression, ranking, forecasting, and predictive modeling.
• Strong understanding of experimentation methodology and applied statistics.
• Experience working with large-scale behavioral datasets.
• Experience leading or mentoring Data Scientists and driving technical initiatives.
• Ability to translate business goals into ML solutions with measurable impact.
• Native Russian language.

Nice-to-have:

• Experience with mobile advertising ecosystems (AdMob, AppLovin, Unity Ads, ironSource, etc.).
• Experience with recommendation systems based on embeddings, collaborative filtering, or learning-to-rank.
• Experience deploying ML models into production.
• Experience with LLMs or GenAI applications.
• Experience with MLOps and cloud platforms (AWS, GCP, Azure).

We offer:

• Competitive salary and benefits package.
• Opportunity to work on high-scale mobile products with millions of users.
• Direct impact on monetization strategy and core product algorithms.
• High level of ownership and autonomy.
• Opportunity to shape the Data Science direction and mentor a growing team.
• Opportunity to work with a talented and passionate team in a creative and dynamic environment.
• Flexible working hours and hybrid/office work options.
• Career growth and professional development opportunities.
• A fun and inclusive company culture that celebrates diversity and creativity.

Join us and let’s create great content together!

Яндекс Маркет помогает миллионам пользователей выбирать товары и совершать покупки.

Наша команда создаёт алгоритмы и инфраструктуру для подбора товаров, интересных пользователю. Мы ежедневно обрабатываем сотни терабайт данных и на их основе формируем персонализированные товарные рекомендации на главной странице, подбираем аналогичные и сопутствующие товары и т. д.

Мы пользуемся методами математической статистики и технологиями машинного обучения: нейросетями, CatBoost, коллаборативной фильтрацией. Активно работаем над технологическим стеком и продуктами вместе с другими командами Яндекса.

ML-инфраструктура и оптимизация производительности

Вам предстоит решать сложные инфраструктурные задачи: от налаживания поставок данных до улучшения производительности: у нас десятки миллионов товаров и пользователей, петабайты данных.

Внедрение нейросетевых моделей

Вы будете внедрять в продакшн нейросетевые модели на основе эмбеддингов: ONNX, HNSW, KServe, Triton.

Развитие алгоритмов ранжирования

Предстоит развивать алгоритмы для подбора и ранжирования товаров: от эвристик и СatBoost до нейросетевых Argus и Gryphon.

Внедрение новых продуктов и технологий

Нужно будет развивать технологическую базу, внедрять новые продукты.

* Работали в аналогичной должности от года
* Хорошо знаете С++, Java или C# и готовы перейти на С++ — основной язык для продакшна
* Разбираетесь в базовых алгоритмах и структурах данных
* Создавали отказоустойчивые системы

* Создавали системы, использующие машинное обучение
* Понимаете метрики ранжирования и специфику рекомендательных систем
* Знаете Python, SQL на больших данных
* На базовом уровне знаете Unix/Linux, Git, контейнеризацию
* Работали со Spark/YT над терабайтами логов
* Занимались распределённым обучением крупных DL-моделей, профилированием, повышали эффективность утилизации GPU