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.
- 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.
#LI-VR2
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Job Family Group:
Risk Management
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Job Family:
Enterprise Risk
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Time Type:
Full time
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Most Relevant Skills
Analytical Thinking, Controls Lifecycle, Credible Challenge, Governance, Policy, Procedure, and Regulation, Risk Management Lifecycle.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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