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.
Required qualifications & skills
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.
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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.
Experience 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.
Apply now to bring your Python and AI development expertise to a role where your work directly strengthens how Citi understands and manages financial risk globally.
For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
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