Nasdaq
From Nasdaq's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
This role is based in Mumbai and operates on a hybrid working model (typically 3 days in office, 2 days remote).
Quantitative Analyst — Front Office Analytics About Calypso (a Nasdaq product) Nasdaq Calypso delivers mission-critical risk, regulatory, and trading technology to the world's largest financial institutions. The platform powers trading and trade processing across every major asset class — FX, rates, equities, credit, commodities, and digital assets — serving hundreds of banks, broker-dealers, asset managers, and central counterparties globally. Our Quantitative Analytics team sits within a global organization of 10,000+ colleagues with offices across North America, EMEA, and APAC. We combine the engineering depth of a leading fintech with the scale, stability, and client reach of a publicly listed market infrastructure leader. This role is based in Mumbai and operates on a hybrid working model (typically 3 days in office, 2 days remote). Role Overview We are hiring a Quantitative Analyst to join our Front Office Analytics team. You will design, implement, and productionize pricing and risk models used directly by our clients' trading desks. This is a hands-on quant role: you will own models end-to-end, from mathematical derivation through C++/Python implementation, performance optimization, testing, documentation, and client support. Our library covers all major asset classes, so you'll have exposure well beyond any single desk.
Develop and maintain pricing, risk, and XVA models across rates, FX, credit, equity, and/or commodities
Translate mathematical specifications into high-performance, well-tested production code
Work directly with clients' quants and traders to calibrate, validate, and extend models to new products and markets
Partner with Engineering on performance (vectorization, GPU/parallel compute, AAD/adjoint sensitivities)
Give to our AI/ML initiatives for model acceleration, calibration, and anomaly detection
Write clear technical documentation and defend methodology in model validation reviews
Required
5+ years as a quantitative analyst in derivatives analytics (any asset class considered)
Strong development skills in C++ (modern C++17/20) and/or Python; comfort with Git, CI/CD, and code review culture
PhD (or equivalent research experience) in Mathematics, Physics, Engineering, Computational Finance, or a related quantitative field
Solid grounding in stochastic calculus, numerical methods (Monte Carlo, PDE, finite difference), and derivative pricing theory
Passion for writing industrial-strength, reusable analytics code
Nice to have
Experience with AAD / algorithmic differentiation libraries
Exposure to XVA, SIMM, FRTB, or IM/VM calculation engines
ML/AI applied to pricing, calibration, or risk (PyTorch, JAX, scikit-learn)
Cloud-native development (AWS / Azure / GCP), containers, Kubernetes
Experience contributing to a vendor or sell-side production analytics library
Competitive base salary and discretionary performance-based bonus
Nasdaq equity (RSUs) and employee stock purchase plan
Comprehensive health, retirement, and wellbeing benefits
Hybrid working, generous leave, and paid learning & conference budget
A global team of quants, engineers, and researchers working on problems that directly move markets
Nasdaq is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Come as You Are
Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities.
We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated.
We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process.
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