Quantitative Developer, AVP (Hybrid)

Citi · Mumbai · Posted 2026-07-18

Tech stack: Python

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About the role

Citi is looking for a Quantitative Developer to build and advance Python-based risk analytics tools and dashboards that sit at the heart of a global stress testing programme. In this role, you will combine deep software engineering expertise with hands-on AI development to deliver solutions that directly inform how Citi measures and manages financial risk at scale. This is an opportunity to work on technically complex, high-impact problems within a collaborative team in Mumbai.
Responsibilities: - Build and enhance risk analytics tools, dashboards, and reporting capabilities that support a firm-wide stress testing programme used to assess financial resilience across global portfolios.
- Design and develop Python-based implementations of risk models, ensuring clean, high-performance code that meets production standards.
- Lead AI-driven development initiatives from prototype through to stakeholder review, translating analytical requirements into working solutions using large language models and AI-assisted tooling.
- Manage the end-to-end integration of risk models and analytics tools with enterprise IT systems, including user acceptance testing and production releases.
- Develop and maintain Stress Loss Calculator infrastructure and other core components that underpin the stress testing platform.
- Gather and incorporate feedback from key stakeholders to refine prototypes and ensure delivered tools meet business and analytical needs.
Qualifications: - Master's degree in a quantitative discipline such as Mathematics, Engineering, or Computer Science.
- 5 or more years of professional software engineering experience with Python as the primary language, ideally gained within the financial services industry.
- Demonstrated ability to write clean, high-performance, and idiomatic Python code that is maintainable in a production environment.
- Applied experience using advanced AI tools and large language models such as Gemini or Claude to design and deliver data and risk analytics solutions.
- Strong analytical and problem-solving skills, with familiarity across financial markets, financial instruments, and risk management methodologies.
- Beneficial skills & qualifications
- Proficiency with AI-powered development tools such as GitHub Copilot to accelerate code generation, debugging, and performance optimization.
- Familiarity with stress testing frameworks or quantitative risk modelling within a financial institution.
- managing UAT processes and coordinating production releases for analytics or model-driven systems.
- What we offer
- At Citi, you will work on technically demanding problems that have real consequences for how a global financial institution manages risk.
- You will be part of a team that values engineering quality, analytical rigour, and the practical application of emerging AI technologies.
- Hybrid working model with 3 days in the office and 2 days working remotely, giving you flexibility alongside meaningful in-person collaboration.
- Access to learning and development resources that support your growth as both a software engineer and a quantitative practitioner.
- Exposure to global risk management programmes, giving you visibility into how financial risk is assessed and managed at an international scale.
- The opportunity to work at the forefront of AI adoption in financial services, applying cutting-edge tools to solve real analytical challenges.
- A performance-driven environment where your technical contributions directly shape the quality and capability of critical risk infrastructure.

Qualifications

- Master's degree in a quantitative discipline such as Mathematics, Engineering, or Computer Science.
- 5 or more years of professional software engineering experience with Python as the primary language, ideally gained within the financial services industry.
- Demonstrated ability to write clean, high-performance, and idiomatic Python code that is maintainable in a production environment.
- Applied experience using advanced AI tools and large language models such as Gemini or Claude to design and deliver data and risk analytics solutions.
- Strong analytical and problem-solving skills, with familiarity across financial markets, financial instruments, and risk management methodologies.
- Beneficial skills & qualifications
- Proficiency with AI-powered development tools such as GitHub Copilot to accelerate code generation, debugging, and performance optimization.
- Familiarity with stress testing frameworks or quantitative risk modelling within a financial institution.
- managing UAT processes and coordinating production releases for analytics or model-driven systems.
- What we offer
- At Citi, you will work on technically demanding problems that have real consequences for how a global financial institution manages risk.
- You will be part of a team that values engineering quality, analytical rigour, and the practical application of emerging AI technologies.
- Hybrid working model with 3 days in the office and 2 days working remotely, giving you flexibility alongside meaningful in-person collaboration.
- Access to learning and development resources that support your growth as both a software engineer and a quantitative practitioner.
- Exposure to global risk management programmes, giving you visibility into how financial risk is assessed and managed at an international scale.
- The opportunity to work at the forefront of AI adoption in financial services, applying cutting-edge tools to solve real analytical challenges.
- A performance-driven environment where your technical contributions directly shape the quality and capability of critical risk infrastructure.

Responsibilities

- Build and enhance risk analytics tools, dashboards, and reporting capabilities that support a firm-wide stress testing programme used to assess financial resilience across global portfolios.
- Design and develop Python-based implementations of risk models, ensuring clean, high-performance code that meets production standards.
- Lead AI-driven development initiatives from prototype through to stakeholder review, translating analytical requirements into working solutions using large language models and AI-assisted tooling.
- Manage the end-to-end integration of risk models and analytics tools with enterprise IT systems, including user acceptance testing and production releases.
- Develop and maintain Stress Loss Calculator infrastructure and other core components that underpin the stress testing platform.
- Gather and incorporate feedback from key stakeholders to refine prototypes and ensure delivered tools meet business and analytical needs.

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