Lead Data Scientist

We are seeking a Lead Data Scientist to drive core modeling execution, including running competitive model bake-offs, selecting champion models, performing model evaluation, and implementing anomaly detection.

Responsibilities Conduct model experimentation and bake-offs across multiple algorithmic families (tree-based regressors, statistical forecasting, deep learning, optimization)
Select and justify the champion model based on cross-validation and business-defined error metrics

Implement anomaly detection algorithms to identify outliers and operational disruptions in historical demand data Track and log experiments using MLflow within the Microsoft Fabric environment

Partner with Data Engineering and BI teams to ensure seamless feature delivery and prediction consumption

Requirements

Advanced degree or equivalent experience in Data Science, Statistics, Operations Research, or Computer Science Expertise in Time Series Forecasting, Machine Learning, and mathematical optimization

Proficiency in Python and modern ML libraries such as LightGBM, XGBoost, and Scikit-learn

Familiarity with Prophet and Optuna

Experience with experiment tracking using MLflow and validation methodologies such as walk-forward CV Professional English proficiency (B2+/C1)
We offer

International projects with top brands

Work with global teams of highly skilled, diverse peers

Healthcare benefits

Employee financial programs

Paid time off and sick leave

Upskilling, reskilling and certification courses

Unlimited access to the Linked In Learning library and 22,000+ courses

Global career opportunities

Volunteer and community involvement opportunitiesEPAM Employee Groups Award-winning culture recognized by Glassdoor, Newsweek and Linked

InEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.