This role pays more than
77%
of similar roles. Most pay
$140,000–$237,500
— the shaded band above.
At the midpoint, this role pays about
$245k
versus about
$189k
for comparable roles.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
The Quantitative Research role involves the research and development of derivatives margin models, including market stress calibration, historical backtesting, system design, and implementation. You will drive client engagement throughout the model development lifecycle while providing ongoing support after deployment. Responsibilities include integrating mathematical models with credit risk management and margin calculation platforms, preparing documentation for internal validation, and serving as a subject-matter expert in regulatory meetings regarding counterparty credit risk and initial margin calculations. The work focuses on quantifying CVA, FVA, PFE, and capital exposures using no-arbitrage pricing theory, stochastic calculus, probability theory, and Monte Carlo simulation methods. You will build portfolio and trade-level models for swaps, options, and exotic derivatives. Technical requirements include implementing these models in C++ and Python while utilizing Valgrind, Intel VTune, and Visual Studio Profiler with CUDA for performance optimization.
Research and develop derivatives margin models including market stress calibration and historical backtesting.
Implement mathematical models for credit risk management and margin calculation platforms.
Manage the end-to-end model development lifecycle, including source code control and release testing.
Provide technical support and gather client feedback throughout the model development lifecycle.
Prepare comprehensive documentation and perform rigorous testing to support internal model validation.
Serve as a subject-matter expert in regulatory meetings regarding counterparty credit risk and initial margin calculations.
Develop portfolio and trade-level margin models for swaps, options, and exotic derivatives.
Optimize model performance using C++, Python, and GPU computing techniques like CUDA.
What we're looking for
Master's degree in Mathematics of Finance, Quantitative Financial Modeling, Computational Finance, Mathematics, Statistics, Physics, or a related field.
At least 2 years of experience in the job offered, as a Quantitative Researcher, or in a related occupation.
Experience using mathematical models including No-arbitrage pricing theory, stochastic calculus, probability theory, and Monte Carlo simulation methods.
Expertise in quantifying counterparty credit risk metrics such as CVA, FVA, PFE, and capital/stressed exposures.
Experience building portfolio and trade-level margin models for financial derivatives including swaps, options, and exotic products.
Proficiency in performing Value-at-Risk (VaR) analysis for exposure and margin model backtesting.
Ability to implement CVA, FVA, PFE, and margin models using C++ and Python.
Experience using profiling tools like Valgrind and Intel VTune, and applying parallel/GPU computing techniques including CUDA.
C++
Python
PyTorch
JAX
CUDA
Kubernetes
Kafka
Spark
Ray
Distributed Systems
Low-latency Engineering
Linux Performance Engineering
order-management systems
market-data normalization
Backtesting
Profiling
Concurrency