Quantitative Trading & Research - Global Clearing - Vice President

Join our global Quantitative Trading & Research (QTR) team, where you'll apply your expertise in Derivatives Modelling, Financial Engineering, Data Science, and Quantitative Development.

As part of JP Morgan's leading QTR Group, you'll innovate with unique analytics and mathematical models, enhancing business practices through automation.

We develop advanced models and methodologies to support the Clearing business, utilizing the Athena quant platform for comprehensive trade and risk management across all asset classes.

Job summary:

As a Vice President Quantitative Researcher in the Quantitative Trading & Research (QTR) Global Clearing team, you will lead the design, delivery, and governance of risk and pricing analytics and models across F&O and OTC derivatives, with a primary focus on risk analytics, Initial Margin (IM) methodology, and production execution.

You will set technical direction and partner closely with the Margin Trading desk, Technology, and Product Development to ship high-impact solutions.

You will also shape our data-led strategy by applying state-of-the-art machine learning to transform risk management and automation across the investment bank.

Job responsibilities


* Own delivery of front-office risk/pricing analytics and margin solutions using internal derivatives libraries, ensuring robust, performant outcomes across D1, F&O, and OTC products; define multi-quarter roadmaps and drive continuous improvement.


* Lead end-to-end initiatives-from problem framing and hypothesis design through prototyping, backtesting, and scalable production deployment-partnering with Trading, QR peers, Technology, and Product to deliver measurable business impact.


* Design and enhance margin and derivative models, including methodology selection, calibration, numerical schemes, benchmarking/backtesting, documentation, and alignment with model risk governance.


* Serve as model owner: manage roadmaps, controls, monitoring/alerts, change management, and responses to Model Risk, Audit, and regulatory reviews; ensure explainability and transparency of assumptions, limitations, and model performance.


* Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms.


* Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best practices (testing, CI/CD, reproducibility), and develop team capability.


* Communicate complex quantitative concepts to non-technical audiences; influence product roadmaps, prioritization, and resourcing via data-driven analysis, scenario studies, and clear articulation of trade-offs.


* Lead development of ML/AI solutions end-to-end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable...