Quantitative Research [Multiple Positions Available]

JPMorgan Chase & Co.; New York (NY); On-site; USD 200,000 - 285,000; Full time

Job summary

JPMorgan Chase & Co. in New York is seeking a Quantitative Researcher to lead end-to-end research, development, and enhancement of derivative pricing and cross-asset diffusion models focused on commodities and FX.

You will test models, prepare documentation, and support trading desks with analytics for P&L attribution, risk decomposition, and hedging evaluation. You will collaborate with front office on structuring new transactions, validating counterparty credit risk metrics, and ensuring pre-

Qualifications

• Master's degree in Financial Engineering, Mathematical Finance, Statistics, or related field required.
• Three years of relevant experience in quantitative research or analytics.
• Strong knowledge of derivative pricing, risk, and trading analytics.

Responsibilities

• Develop end-to-end derivative pricing and cross-asset diffusion models.
• Conduct model testing and documentation for governance and reviews.
• Provide quantitative support for P&L attribution, risk decomposition, and hedging evaluation.
• Collaborate with front office on structuring and onboarding new transactions and asset types.
• Interface with credit risk management for pre-trade approval and post-trade exposure monitoring.

Skills

No-arbitrage pricing theory

Stochastic calculus

Probability theory

Measure theory

Calibration of multi-factor models

High-performance computing

Counterparty credit risk metrics

Econometric methods

Machine learning for analytics

Education

Master's degree in Financial Engineering/related field

Tools

C++

Job description

DESCRIPTION:

Duties: Drive end-to-end research, development, and enhancement of derivative pricing and cross-asset diffusion models focused on commodities and foreign exchange, including model testing and preparation of model documentation. Conduct ongoing model performance testing and serve as a point of contact during model review and re-review processes. Provide quantitative support to trading desks through analytical methodologies for profit-and-loss attribution, risk decomposition, and hedging evaluation. Develop frameworks that improve transparency of model behavior and risk factor dynamics. Collaborate with front office stakeholders on structuring and onboarding new transactions and asset types, including independent assessment and validation of counterparty credit risk metrics and exposure profiles. Interface with credit risk management functions to support pre-trade approval workflows and post-trade credit exposure monitoring in alignment with enterprise risk governance frameworks.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Financial Engineering, Mathematical Finance, Statistics, or related field of study plus three (3) years of experience in the job offered or as Quantitative Research, Quantitative Analyst, or related occupation.

Skills Required: This position requires three (3) years of experience with the following: Applying no-arbitrage pricing theory, stochastic calculus, probability theory, measure theory, reduced-form intensity models, and continuous-time stochastic processes to quantitative modeling and analytics across commodities such as North America and European Oil, Power, Gas, Emission, Base and Precious Metals, and foreign exchange markets including G10 and major emerging market currencies; Calibrating multi-factor models with seasonality and mean-reversion features using optimization algorithms to fit model parameters to observed market data; Developing and maintaining high-performance computational libraries using C++, including memory management, parallelization strategies, Monte Carlo methods, optimization methods, interpolation and approximation methods, stochastic differential equations, and regression methods; Quantifying counterparty credit risk metrics and regulatory capital measures to support risk management and governance processes; Constructing and deploying analytical tools for profit and loss attribution, risk decomposition, and hedging strategy evaluation using econometric methods, statistical learning, machine learning models, and automated workflow frameworks to support trading and risk management.

Job Location: 270 Park Ave, New York, NY 10017.

Full-Time. Salary: $200,000 - $285,000 per year.