Senior Risk Data Scientist

Key Responsibilities

• Design, development, implementation, and continuous improvement of machine learning (ML) and statistical models for risk assessment and other banking applications.
• Collaboration with IT and business teams to integrate models and solutions into the Bank's operational processes.
• Researching modern machine learning (ML) and artificial intelligence (AI) methods and proposing their practical applications in the field of risk management.
• Preparation of reports and dashboards to transform complex analysis results into practical and actionable business insights.
• Ensuring proper documentation, reproducibility, deployment, and explainability of models and solutions.
• Performing other duties as defined by the Bank's internal regulations or assigned directly by the manager.

Required Qualifications

• At least 5 years of work experience in Data Science, machine learning (ML), statistical modeling, or Predictive Analytics. Experience in banking, credit scoring, or financial risk will be considered a significant advantage.
• Higher education in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
• Advanced knowledge of Python (pandas, NumPy, scikit-learn, and other ML libraries) and advanced knowledge of SQL, with experience working with relational databases and large-scale data.
• Deep knowledge of machine learning model evaluation and validation methodologies, particularly regarding tree-based and boosting methods.
• Experience with version control and vibe-coding skills will be considered an advantage.
• Good knowledge of English and Russian.

Personal Attributes

• Strong analytical thinking and a structured approach to problem-solving.
• Ability to independently manage complex problems and take responsibility for solutions.
• Developed communication skills, including the ability to present technical results in an understandable way to non-technical stakeholders and to collaborate effectively with different teams.
• Ability to correctly prioritize and meet deadlines, ensuring reliable results.
• Willingness to share experience and provide mentorship to junior specialists.