01Overview
Job Description:
Data Scientist Banking and Risk Management
Role Summary
The Data Scientists will design AI/ML models for banking and risk management, driving innovation and enhancing operational efficiencies for financial institutions.
Key Responsibilities
Develop AI/ML models for credit scoring, fraud detection, and risk assessment in banking.
Analyze large datasets from banking systems to identify risk trends and insights.
Build predictive analytics solutions for portfolio performance and default probabilities.
Integrate AI/ML solutions into risk management frameworks for regulatory reporting.
Collaborate with financial institutions to optimize risk strategies using advanced data science tools.
Required Skills
Proficiency in Python, R, and machine learning frameworks (TensorFlow, PyTorch).
Knowledge of banking risk metrics and regulatory requirements (e.g., Basel, IFRS 9).
Experience with financial data analysis and visualization tools (e.g., Tableau, Power BI).
Bachelors/Masters in Data Science, Computer Science, or Financial Technology.
Strong understanding of banking processes and risk management practices. .
