Quantitative Developer

Location: London, Hybrid

About the Company

Our client is a prominent global financial institution operating across multiple markets, offering investment banking, corporate banking and risk management services. Known for its strong regulatory discipline and commitment to innovation, the firm maintains robust infrastructure and technology teams that support critical quantitative, risk and analytics functions across its international operations.

Job Description

The Quantitative Analytics team within the investment banking division is seeking a skilled and motivated Credit Quant Developer to support a high-priority migration of risk model code. This role focuses on quantitative risk (Market, Credit and Interest Rate Risk) rather than front-office pricing, and plays a vital part in enhancing the stability and adaptability of the firm’s credit banking book models.

You will be responsible for translating and restructuring existing model components, primarily migrating code from R to Python - ensuring the newly implemented versions are efficient, well-organised and maintainable. This role requires strong technical ability, excellent problem solving skills and a solid foundation in econometrics and time-series methodologies.

Key Responsibilities:

• Lead the migration and translation of quantitative model code, focusing heavily on transitioning existing R models into Python.
• Develop and implement clean, logical and scalable code structures that can be easily adapted to evolving business and regulatory needs.
• Apply strong econometric knowledge to handle model challenges, identifying improved coding solutions when direct translation is not suitable.
• Work collaboratively within the Credit QA team to produce well-documented, thoroughly tested and production-ready model code.

Ideal Qualifications

• Strong programming ability in Python, including experience using GIT or similar version-control tools.
• Solid understanding of econometrics, including foundational concepts such as linear regression, time-series analysis and factor analysis.
• Experience working within the banking or broader financial services sector, ideally within a regulated environment
• A critical, analytical mindset with the ability to review and challenge model behaviour and code quality.

Nice to have

• Familiarity with R / R-Studio or the ability to comfortably interpret R code, which supports the migration process.
• Understanding of C++ for potential cross-team collaboration.
• Exposure to quantitative risk domains including Market Risk, Credit Risk or Interest Rate Risk.
• Advanced econometric knowledge, such as experience with capital models, meta-models or correlation modelling.

The Quantitative Analytics team within the investment banking division is seeking a skilled and motivated Credit Quant Developer to support a high-priority migration of risk model code. This role focuses on quantitative risk (Market, Credit and Interest Rate Risk) rather than front-office pricing, and plays a vital part in enhancing the stability and adaptability of the firm’s credit banking book models.

You will be responsible for translating and restructuring existing model components, primarily migrating code from R to Python - ensuring the newly implemented versions are efficient, well-organised and maintainable. This role requires strong technical ability, excellent problem solving skills and a solid foundation in econometrics and time-series methodologies., * Strong programming ability in Python, including experience using GIT or similar version-control tools.

• Solid understanding of econometrics, including foundational concepts such as linear regression, time-series analysis and factor analysis.
• Experience working within the banking or broader financial services sector, ideally within a regulated environment
• A critical, analytical mindset with the ability to review and challenge model behaviour and code quality., * Familiarity with R / R-Studio or the ability to comfortably interpret R code, which supports the migration process.
• Understanding of C++ for potential cross-team collaboration.
• Exposure to quantitative risk domains including Market Risk, Credit Risk or Interest Rate Risk.
• Advanced econometric knowledge, such as experience with capital models, meta-models or correlation modelling.

Our client is a prominent global financial institution operating across multiple markets, offering investment banking, corporate banking and risk management services. Known for its strong regulatory discipline and commitment to innovation, the firm maintains robust infrastructure and technology teams that support critical quantitative, risk and analytics functions across its international operations.