{"id":3000042,"url":"https://alion.io/job/astrazeneca-russia-middlesenior-data-scientist-2","title":"Middle/Senior Data Scientist","company":{"id":66505,"name":"AstraZeneca Russia","domain":"astrazeneca.ru","url":"https://alion.io/company/astrazeneca-ru","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HeadHunter","truth_index":{"grade":"B","score":79,"open_postings":19,"ghost_share":0.211,"stale_share":0,"repost_share":0.579,"time_to_fill_p50_days":30,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Moscow, 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прогноз с доверительными интервалами.\n Детектирование аномалий - выявление отклонений от прогнозов, генерация алертов в реальном времени.\n Сценарное моделирование - симуляция бизнес-сценариев и расчёт влияния на прибыльность, запасы, доступность.\n Генерация action plans - автоматическое формирование планов действий на горизонте до 12/24/36 месяцев.\n Создание и поддержка специализированных датасетов для адаптации моделей под прогнозирования и моделирования продаж.\n Оптимизация моделей для production-среды (квантизация, дистилляция).\n Разработка стандартов и процессов обучения моделей.\n Ты идеально нам подходишь, если у тебя есть:\n Оконченное профильное высшее образования.\n Глубокое понимание современных архитектур и методов обучения языковых моделей.\n Глубокое понимание след. библиотек - CatBoost, LSTM, Prophet, Croston, ансамблевые методы и др.\n Практический опыт файнтюнинга различных LLM под продуктовые задачи (SFT, PEFT, RLHF, LoRA, PPO, DPO, GRPO).\n Уверенное владение Python и экосистемой ML и LLM-инструментов (PyTorch, TRL, Accelerate, PEFT, Transformers, VLLM, scikit-learn, pandas, NumPy, etc).\n Живой интерес к сфере GenAI, опыт работы с популярными вендорными и open-source моделями (Qwen, Llama, DeepSeek, GPT-OSS).\n Практический опыт создания решений на базе LLM (prompt engineering, RAG, function calling, structured outputs, reasoning, agents).\n Понимание методов оценки качества LLM (бенчмарки, human eval, LLM-as-Judge) и метрик для различных NLP-задач.\n LLM и агентные системы - опыт с OpenAI/Gemini/Claude API, Microsoft Copilot Studio, мультиагентные архитектуры.\n Хорошее знание метрики прогнозирования - WMAPE, MAPE, MAE, bias и др.\n Умение балансировать исследовательские задачи и бизнес-требования.\n Будет плюсом: опыт внедрения LLM-решений в продакшн.\n Успешному кандидату мы готовы предложить:\n Возможность строить карьеру в динамичной атмосфере лидирующей инновационной компании с одним из сильнейших портфелей препаратов в отрасли.\n Компенсация мобильной связи.\n Комфортный и стильный офис в Москва-сити.\n Гибридный формат работы(3 офис /2 дом или 4 офис/1дом).","description_format":"text","description_chars":2428,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"Russian","level":"Advanced (C1)","optional":false}]},"benefits":[],"hiring_locations":[{"name":"Russia","iso":"RU","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Prescription Drugs","Oncology Therapeutics","Rare Disease Therapeutics","Cardiometabolic Therapeutics"],"lifecycle":[{"event":"open","at":"2026-10-21T11:52:22Z"}],"visa":[],"liveness":{"score":81,"band":"hot","label":"Hiring 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