Data Scientist – Banking Risk & Analytics

About the role

Deeplight AI is seeking a Data Scientist with deep banking domain knowledge to design, develop, and deploy statistical models for regional financial institutions. You will work across Treasury, Wholesale Banking, and Corporate Lending to turn complex data into actionable risk solutions.

Key responsibilities

• Build advanced risk models such as Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) for corporate lending and treasury operations.
• Develop analytical modules for Risk‑Adjusted Return on Capital (RAROC) and capital optimisation frameworks.
• Ensure models comply with Basel III/IV, stress‑testing and regulatory capital requirements.
• Write clean, modular Python code and participate in peer code reviews.
• Collaborate with client risk officers, business analysts and technical leads to translate requirements into robust quantitative solutions.

Required profile

• Strong background in data science, statistical modelling and quantitative finance.
• Demonstrated experience with banking risk domains and regulatory frameworks.
• Ability to communicate complex analytical results to both technical and business audiences.
• Proven track record of delivering production‑ready models in a consultancy environment.

Required skills

• Python programming for data analysis and model development.
• Statistical modelling techniques applied to credit risk and capital management.

What we offer

• Opportunity to work on high‑impact projects for leading regional banks.
• Collaborative environment with deep expertise in AI and finance.
• Exposure to cutting‑edge risk analytics and regulatory challenges.