Data Scientist
Core
Design, develop, and deploy statistical risk models and data-driven solutions for corporate banking, wholesale banking, and treasury operations.
Role type
Senior IC data scientist (quantitative finance/risk)
Builds
Production statistical models, risk frameworks, and regulatory capital solutions
Domain
Financial services / Banking / Quantitative risk
Deliverable
production ML models
Required skills
Statistical modeling, Python (NumPy, SciPy, Pandas, Scikit-learn, Statsmodels, PyTorch/TensorFlow), Basel III/IV framework knowledge, Risk-Adjusted Return on Capital (RAROC) optimization, Probability of Default (PD) modeling, Loss Given Default (LGD) modeling, Exposure at Default (EAD) modeling, Stress testing protocols
Preferred skills
Causal analysis, Transformers/sequence models, PySpark/Spark/Dask, Interactive dashboards (Streamlit, Plotly)
Responsibilities
Design and implement statistical risk models for corporate lending and liquidity management; Build analytical modules for capital optimization; Apply regulatory capital rules and stress testing frameworks; Write clean, modular Python code and participate in peer code reviews; Partner with client risk officers to decompose requirements and present quantitative findings
Seniority
Senior, hands-on IC
