Quantitative Developer / Market Risk

Motion Recruitment; Jersey City (NJ); Hybrid; USD 160,000 - 210,000; Full time

Job summary

Motion Recruitment Partners LLC in Jersey City, NJ, seeks a Quantitative Developer (Market Risk) for a 6-month contract with strong extension potential. Hybrid work is required, with 3 days onsite per week on a global bank project.

You will architect and run a massive distributed compute grid on AWS/GCP, implementing pricing models and ensuring high availability in a high-pressure environment.

Qualifications

• A degree in Computer Science, Engineering, or a related technical field.
• 10+ years of professional experience with large-scale compute grids.
• Expert-level experience with AWS or GCP including batch processing, containers, and serverless.
• Docker and Kubernetes expertise.
• Strong programming skills in C++ and Python.
• Experience in finance-related risk pricing (Monte Carlo, VaR, XVA) is valued.
• Background in distributed systems, IaC, and performance tuning.
• Excellent problem solving and cross-team communication.

Responsibilities

• Architect and manage a massive distributed compute grid on public clouds for pricing models.
• Design orchestration to distribute millions of pricing tasks across cores.
• Deploy and version control a library of pricing models in a distributed environment.
• Monitor and optimize cloud grid performance, cost, and resources.
• Collaborate with quant dev teams to integrate pricing models into production.
• Engineer data logistics for market data, trade data, and model configurations.
• Ensure pricing engine is highly available and meets recovery objectives.

Skills

C++

Python

Cloud (AWS/GCP)

Docker

Kubernetes

Monte Carlo

VaR Pricing

Distributed systems

Performance tuning

IaC

Education

Bachelor's degree in CS/Engineering

Tools

AWS

GCP

Job description

Grow your career as a Quantitative Developer (Market Risk)with an innovative global bank in Jersey City, NJ. Contract role with strong possibility of extension. Will require working a hybrid schedule 3 days onsite per week.

Join one of the world's most renowned global banks and trusted brand with over 200 years of continuously evolving financial services worldwide. You will work alongside some of the smartest minds in the industry who are excited to share their knowledge and to learn from you.

Contract Duration: 6Months

Required Skills & Experience

• A degree in Computer Science, Engineering, or a related technical field.
• 10+ years of professional experience with a proven track record of designing, building, and running applications onmassive-scale compute grids.
• Expert-level, hands-on experience with at least one major public cloud provider (AWSorGCP), including their batch processing, container, and serverless offerings.
• Deep expertise in containerization and orchestration technologies (Docker, Kubernetes).
• Strong programming skills in languages common to high-performance computing, such asC++andPython.
• Prior experience in a similar role within the financial industry (e.g., running large-scale Monte Carlo simulations, VaR calculations, or XVA pricing grids) is highly desirable.
• A strong background in distributed systems, performance tuning, and infrastructure-as-code principles.
• Exceptional problem-solving skills, with an ability to diagnose and resolve complex issues in a high-pressure, large-scale environment.
• Excellent communication skills and the ability to work effectively with quantitative research, trading, and risk management teams.

What You Will Be Doing

• Architect, build, and manage a massive-scale, distributed compute grid on public cloud platforms (AWS, GCP) for running financial pricing models.
• Design and implement the orchestration layer responsible for distributing millions of pricing tasks efficiently across hundreds of thousands of CPU/GPU cores.
• Deploy, manage, and version control a diverse library of quantitative pricing models, ensuring they run optimally in a distributed environment.
• Obsessively monitor and optimize the performance, cost, and resource utilization of the cloud grid, driving continuous efficiency improvements.
• Collaborate with quantitative development teams to seamlessly integrate new and updated pricing models into the production grid.
• Engineer the data logistics to ensure that the correct market data, trade data, and model configurations are available for every calculation at runtime.
• Ensure the pricing engine is highly available, resilient, and capable of meeting stringent recovery time objectives.