in a large company.

The company considers candidates only from Russia. Salary: discussed individually. Work format: Remote, Hybrid, Office (Moscow, Krasnodar) Position level: Senior

Tech Stack: Machine Learning (OR ML and Data Science), Python, Airflow, PostgreSQL, ClickHouse, Kubernetes

🔷Tasks: Develop demand forecasting and price elasticity models; Research approaches to causal inference, uplift modeling, and price change effect estimation; Design time-based validation, backtesting, and business quality metrics; Work with uncertainty, confidence, intermittent demand, cold start, and long-tail SKUs; Develop logic for optimal price selection considering business constraints; Organize plan/fact evaluation and model quality monitoring; Participate in the design of feature engineering, batch training, and batch inference on large data volumes; Conduct design reviews, code reviews, and mentor ML specialists in the team.

🔷Mandatory Requirements: 3+ years of experience in classical ML; Strong foundation in classical ML, statistics, and tabular data handling; Experience with forecasting, time series, and gradient boosting: LightGBM, CatBoost, or XGBoost; Understanding of causal inference and experimental design; Experience in bringing ML models to production; Proficient in Python and SQL; Understanding of time-based validation, data leakage, calibration, and uncertainty estimation; Experience with Airflow or a similar orchestrator; Understanding of distributed data processing principles, partitioning, and computation optimization; Ability to link ML metrics to measurable business impact; Experience in retail, e-commerce, pricing, or demand forecasting; Practical experience with PySpark, Trino, Iceberg, S3, dbt, or ClickHouse; Experience with price optimization, hierarchical forecasting, or operations research; Experience in building ML monitoring and conducting A/B tests.