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Salary
≈ $25k – $61k per year (Estimated)
Location
Hybrid (Moscow, Russia)

Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Oct 12, 2026. BetBoom scores A on the Alion truth index.

Overview
Company
Impact
Profile match
BetBoom is a Russian gambling and sports betting company headquartered in Moscow and established in 2010. The company provides a platform for online sports and esports wagering, alongside a network of physical betting shops located throughout the country. Operating under a license from the Federal Tax Service, it serves the domestic market with a focus on digital innovation and sponsorship of major sports teams and events.

Мы ищем Data Scientist в команду, которая занимается разработкой ML-решений для бизнес-задач. Основной фокус роли - полный цикл работы с моделями: от исследования данных и проверки гипотез до вывода решений в production и дальнейшего мониторинга.

Чем предстоит заниматься:

  • Формулировать и проверять гипотезы на основе данных, проводить эксперименты (A/B-тесты, multi-armed bandit, sequential testing);

  • Разрабатывать ML-решения для различных бизнес-задач: от MVP до полноценных production-моделей;

  • Участвовать в полном цикле разработки моделей: постановка задачи, подготовка данных, построение решения, внедрение и мониторинг;

  • Работать совместно с аналитиками и data-инженерами над построением признаков, data pipeline и процессами деплоя моделей;

  • Проводить исследование данных (EDA), очистку, подготовку и визуализацию данных.

Мы ожидаем:

  • Опыт работы с реляционными и колоночными базами данных (PostgreSQL, ClickHouse, Greenplum);

  • Уверенное владение Python и основными ML-библиотеками (pandas, NumPy, scikit-learn и др.);

  • Знание классического машинного обучения: задачи классификации и регрессии, алгоритмы, метрики качества, особенности применения;

  • Понимание математической статистики и теории вероятностей: A/B-тестирование, статистические критерии, p-value, ошибки первого и второго рода, статистическая мощность;

  • Опыт работы с данными: подготовка выборок, feature engineering, отбор факторов;

  • Практический опыт работы с LLM (prompt engineering, skills);

  • Опыт командной разработки с использованием Git и code review;

  • Умение формулировать бизнес-задачу и переводить её в ML-решение.

Будет плюсом:

  • Отличное знание SQL: оконные функции, CTE;

  • Опыт работы с causal inference и uplift-моделированием;

  • Навыки написания чистого, тестируемого и поддерживаемого кода.

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