{"id":3804059,"url":"https://alion.io/job/bank-centercredit-data-scientist-ml-engineer","title":"Data Scientist / ML Engineer","company":{"id":47267,"name":"Bank CenterCredit","domain":"bcc.kz","url":"https://alion.io/company/bank-centercredit","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HeadHunter","truth_index":{"grade":"D","score":45,"open_postings":4,"ghost_share":0.75,"stale_share":0,"repost_share":1,"time_to_fill_p50_days":10,"computed_at":"2026-11-06T05:58:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Almaty, Kazakhstan"],"countries":["KZ"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Feature Store","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"DVC","optional":true},{"name":"Feast","optional":true},{"name":"Function Calling","optional":true},{"name":"GitHub Actions","optional":true},{"name":"GitLab CI","optional":true},{"name":"H2O.ai","optional":true},{"name":"MLFlow","optional":true},{"name":"Optuna","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-11-05T12:45:28Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-05T20:39:07Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Обязанности:\n Разработка и поддержка общих ML-компонентов для команды: пайплайнов подготовки данных, расчёта признаков (Feature Engineering), стандартных метрик и отчётов по моделям.\n\n Создание и развитие внутренней AutoML-платформы для автоматизации разработки и обучения риск-моделей.\n\n Построение и развитие Feature Store, обеспечение контроля качества данных и корректности расчёта признаков.\n\n Автоматизация процессов разработки, обучения, тестирования и мониторинга ML-моделей.\n\n Внедрение LLM-агентов в рабочие процессы команды для помощи в построении моделей, анализа результатов и подготовки технической документации.\n\n Участие в развитии инженерных практик команды: проведение Code Review, внедрение тестирования, CI/CD и повышение качества разрабатываемых решений.\n\n Требования:\n Опыт работы в Data Science или ML-разработке от 2 лет.\n\n Уверенное владение Python: знание ООП, разработка модулей и пакетов, умение читать и анализировать чужой код.\n\n Хорошее знание SQL: сложные JOIN, оконные функции, работа с большими объёмами данных.\n\n Понимание классических алгоритмов машинного обучения: бустинги, логистическая регрессия, метрики качества моделей (Gini, ROC-AUC), методы кросс-валидации и предотвращения переобучения.\n\n Практический опыт работы с Git: ветки, Merge Request, разрешение конфликтов и участие в Code Review.\n\n Опыт работы с оркестраторами (Airflow или аналоги), написания и отладки DAG, а также разработки воспроизводимого кода с фиксацией зависимостей, тестированием ключевой логики и логированием.\n\n Будет преимуществом:\n\n Опыт работы в банковской сфере, в частности с риск-моделями, скорингом, PD и валидацией моделей.\n\n Опыт использования AutoML-инструментов (LightAutoML, Optuna, H2O) или автоматизации процессов обучения моделей.\n\n Понимание архитектуры Feature Store и опыт работы с Feast или собственными решениями.\n\n Опыт работы с MLflow или DVC для трекинга экспериментов и версионирования моделей.\n\n Практический опыт настройки CI/CD (GitLab CI, GitHub Actions).\n\n Опыт работы с LLM: RAG, агенты, Function Calling и структурированный вывод; 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