Main responsibilities:
• Develop complex ML models for Credit Risk Department: credit application scorecard, collection scorecard, anti-fraud scorecard, etc.
• Lead complex ML projects from initial business discussion to deployment and monitoring.
• Work with different stakeholders during the project: Data Engineers, Risk Managers, DevOps, MLOps, Data Architects.
• Prepare and analyze complex datasets to make ad-hoc analysis.
• Interpret and communicate clearly complex ML solutions to non-technical stakeholders and management.
• Participate in building feature store and discuss ideas/insights to improve ML models.
• Assist in professional growth of junior and middle Data Scientist and Analysts.
Main requirements:
• 3+ years of experience in Data Science field.
• Excellent knowledge of Tree-based and Logistic Regression algorithms.
• Strong Proficiency in Python, SQL. Main packages: Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn, XGBoost (other tree-based packages)
• Knowledge of English (C1) and Russian (B2) languages.
• Bachelor’s degree in STEM field: Science, Technology, Engineering, or Mathematics.
• Working experience at Retail banks with credit risk knowledge would be a huge advantage.