ML Engineer/Data Scientist

Що робити

• Develop, train, and validate ML models for applied business problems, including forecasting, classification, ranking, recommendations, anomaly detection, and risk assessment.
• Perform exploratory data analysis (EDA), formulate and validate hypotheses, and design appropriate metrics and experiments.
• Build feature engineering and data preparation pipelines using pandas and Polars.
• Work with gradient boosting algorithms such as CatBoost, XGBoost, and LightGBM, including hyperparameter tuning, cross-validation, overfitting prevention, and data leakage control.
• Take ML models from prototype to production, including packaging, deployment, quality and data-drift monitoring, and retraining.