Quantitative Developer / Market Risk

Motion Recruitment Partners LLC; Jersey City (NJ); Hybrid; USD 180,000 - 250,000; Full time

Job summary

Global Bank in Jersey City, NJ seeks a Quantitative Developer (Market Risk) for a contract role with hybrid work 3 days onsite per week. The position focuses on designing and operating a massive-scale compute grid on AWS/GCP to run pricing models and risk analytics.

You will deploy and manage a library of pricing models, optimize performance and cost, and collaborate with risk, trading, and research teams to ensure availability and accuracy of pricing results.

Qualifications

• Degree in Computer Science, Engineering, or related field.
• 10+ years in building and operating large-scale compute grid systems.
• Expert experience with public cloud platforms and batch processing.
• Deep containerization and orchestration expertise (Docker, Kubernetes).
• Strong C++ and Python programming skills for HPC workloads.
• Experience in financial domain pricing grids and risk calculations is desirable.
• Solid distributed systems, performance tuning, and IaC knowledge.
• Excellent communication with quantitative research, trading, and risk teams.

Responsibilities

• Architect and manage a massive distributed compute grid on public clouds.
• Design orchestration to distribute millions of tasks across CPU/GPU cores.
• Deploy and version control a library of pricing models for distributed use.
• Monitor cost, performance, and resource utilization; drive efficiency.
• Collaborate with quantitative teams to integrate pricing models.
• Ensure data logistics for market, trade data and model configurations.
• Maintain high availability and disaster recovery readiness.

Skills

Cloud (AWS/GCP)

C++

Python

Monte Carlo

VaR/XVA knowledge

Distributed systems

High-performance computing

Data orchestration

Cost optimization

Communication

Education

Bachelor degree in CS/Engineering

Tools

Docker

Kubernetes

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.