Senior Quant Model Developer - Specialized Lending

Your role

Are you interested in quantitative risk modelling and knowledgeable of statistical, mathematical and econometrical models used in the financial industry? Are you an innovative thinker who likes to challenge the status quo and apply new analytical techniques to solve quantitative problems?

At UBS, we re-imagine the way we work, the way we connect with each other – our colleagues, clients and partners – and the way we deliver value. Being agile will make us more responsive, more adaptable, and ultimately more innovative.

We’re looking for a Quantitative Risk Modeler to:
• develop and maintain Pillar 1 IRB Credit Risk models (PD, LGD, Slotting), including conceptual development, data analysis, prototype coding, documentation and support in the interaction with regulatory and audit stakeholders
• assess model performance by defining and performing quantitative tests and investigating potential gaps
• independently interact with senior Risk Control stakeholders to ensure that the models are correctly used and that they reflect the views of subject matter experts.
• collaborate with other quantitative analysts to share insights and work closely with cross-functional team members to ensure the correct implementation of models in productive environments
• ensure escalation and disclosure of any information of which applicable regulators would reasonably expect notice

Your team

You’ll be working in the CH & US Mortgages, Corporates & Specialized Lending Capital Models as a member of the Specialized Lending Capital Models team in Mumbai focusing on the development of Pillar 1 Credit Risk models for Specialized Lending products. We’re an international team with members in Switzerland, Poland, India with a diverse mix of seniorities and backgrounds.

Your expertise

• ideally 8+ years of quant modelling experience within the finance sector, with strong know-how in basic modeling concepts (e.g., logistic regression, decision trees)
• previous experience with Credit Risk modeling (Pillar 1, stress testing) and the Basel regulatory framework
• experience in low-default and/or bespoke portfolios is a plus
• proficient in SQL and R/Python
• self-driven, organized and detail-oriented with a solid understanding of banking industry
• Master’s/PhD degree or equivalent in a quantitative field (mathematics, statistics, physics, computer science or engineering etc.)
• You’re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment – validating outputs and aligning with policies, risk standards, and ethical use.