Data Scientist

Ostrovok • Russian: C1 • Python • SQL • 1 month ago
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Salary
≈ $27k – $60k per year (Estimated)
Location
In office (Moscow)
Employment
Full-Time
Overview
Company
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Ostrovok

Ostrovok is an online travel company headquartered in Moscow, Russia, and founded in 2010. The company runs a hotel booking service for Russian-speaking travellers and operates the RateHawk business-to-business platform that supplies accommodation inventory to travel agencies worldwide. It sits within the Emerging Travel Group and connects to hotel chains, wholesalers, and channel managers across many countries.
ostrovok.ru • HQ: Moscow, Russia • Marketplaces • Commerce • Travel Agencies • Travel & Tourism • Travel Technology • Hotels & Resorts • 51-200 employees • Est. 2010

Навыки: Apache Airflow, TensorFlow, Python, PyTorch. Специализации: Ученый по данным.

Задачи, над которыми предстоит работать:

  • Поиск гипотез для улучшения релевантности поисковой выдачи
  • Разработка новых признаков, обучение моделей ранжирования
  • Проектирование и проведение A/B-тестов, вывод решений в продакшен
  • Улучшение эксплуатационных характеристик ML-решений: наблюдаемость, надёжность, эффективность

Мы ожидаем, что ты имеешь опыт:

  • Ведения ML-проектов end-to-end в продакшене (от постановки задачи до поддержки)
  • Отличного понимания классического ML: feature engineering, бустинги, классификация/регрессия, кросс-валидация, подбор порогов, калибровка
  • Работы с поисковыми или рекомендательными системами
  • Работы с DL (PyTorch/TensorFlow): fine-tuning, инференс моделей
  • Написания Python production-качества: читаемый код, тесты на критичные компоненты, упаковка модели/артефактов и интеграция в сервис
  • Мониторинга ML-систем: метрики качества, дрейф данных, алерты, диагностика и регламенты поддержки
  • Уверенной работы с SQL: самостоятельная сборка датасетов, joins, window functions
  • Интерпретируемости моделей и анализа ошибок
  • Использования инструментов трекинга экспериментов: MLflow, W&B, DVC или аналогов
  • Работы с оркестрацией и пайплайнами (Airflow / Prefect / Dagster) и продвинутыми data-процессами
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