Quantitative Research

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$200,000–$285,000 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $187k
This role $242k
$123k most similar roles pay here $302k

This role pays more than 78% of similar roles. Most pay $140,000–$234,612 — the shaded band above. At the midpoint, this role pays about $242k versus about $187k 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 1174 open roles on FindRole.

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At a glance

TL;DR · Quantitative Research

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The Quantitative Research role involves developing state-of-the-art analytics and risk management tools specifically for margin and counterparty credit risk. Working within the team, you will collaborate with the XVA modeling group to design and implement cutting-edge quantitative methods while providing essential modeling support to end users in the Collateral Management and Optimization groups. Your daily responsibilities include managing the full model development lifecycle from initial implementation through deployment and release testing. You will utilize High Performance Computing, cloud computing, GPU technologies, and automatic differentiation to automate data analytics and improve internal processes. Required technical skills include implementing models in C++ and Python, performing statistical analysis in Excel, and researching derivative pricing and margin calculations. The role focuses on solving complex problems related to risk management and the technical challenges of financial modeling.

Skills

C++ Python High Performance Computing GPU Automatic Differentiation Cloud Computing Data Analytics Excel Quantitative Finance Derivative Pricing Risk Management Model Development Lifecycle Statistical Analysis Object-Oriented Programming

What you'll do

  • Develop state-of-the-art analytics and risk management tools for counterparty credit risk and margin.
  • Design and implement cutting-edge quantitative methods and analytical tools for derivative pricing.
  • Support and backtest margin models to ensure accuracy.
  • Implement quantitative models using object-oriented programming languages like C++ and Python.
  • Provide technical support by explaining and troubleshooting quantitative models for trading functions and risk managers.
  • Utilize High Performance Computing (HPC) technologies, including cloud computing, GPU, and automatic differentiation.
  • Automate and apply data analytics to improve internal processes.
  • Manage the full model development lifecycle from initial implementation to deployment and release testing.

What we're looking for

  • Master's degree in a quantitative field such as Computational Finance, Math, Physics, or Computer Science plus 2 years of relevant experience.
  • PhD in a quantitative field such as Computational Finance, Math, Physics, or Computer Science (alternative to Master's and experience).
  • Experience researching and developing quantitative finance models for derivative pricing and margin calculations.
  • Experience supporting and backtesting margin models.
  • Experience supporting trading functions and risk managers by explaining and troubleshooting quantitative models.
  • Experience implementing quantitative models in object-oriented programming languages including C++ and Python.
  • Experience retrieving financial data and performing statistical analysis using Python and Excel.

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