Quantitative Developer with Python

Required Education

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
  
  

Required Qualifications/Skills/Experience

• 8+ years of Overall professional experience in Quant/Quantitative Development, Quantitative Research etc, or a related field.
• Client needs candidates with more spark and distributed programming hands on experience.
• Hands-on experience with at least one major public cloud provider (AWS or GCP), including batch processing, container, and serverless services.
• Experience in containerization and orchestration technologies, including Docker and Kubernetes.
• Strong programming skills in Python.
• Strong background in distributed systems, performance tuning, and Infrastructure-as-Code (IaC) principles.
• Exceptional problem-solving skills with the ability to diagnose and resolve complex issues in high-pressure, large-scale environments.
• Excellent communication skills with the ability to collaborate effectively with quantitative research, trading, and risk management teams.
  
  

Preferred Qualifications/Skills/Experience

• Prior experience in a similar role within the financial industry.
• Experience supporting large-scale Monte Carlo simulations, VaR calculations, or XVA pricing grids.
  
  

Overview

Join a team responsible for building and operating one of the largest high-performance computing (HPC) pricing grids in the financial industry. As a Quant Engineer, you will lead the development, deployment, scaling, and optimization of a massive distributed pricing engine running on AWS or GCP. You will operationalize sophisticated quantitative pricing models, enabling millions of trades to be valued across thousands of market scenarios with exceptional speed, reliability, and efficiency. This role requires expertise in cloud computing, distributed systems, Kubernetes, Docker, C++, Python, and large-scale infrastructure. You will partner closely with quantitative developers, trading, and risk management teams to deliver a highly available, resilient, and performance-optimized platform that powers the firm's next-generation risk management capabilities and supports critical regulatory requirements.

Job Duties

• Architect, build, and manage a massive-scale distributed compute grid on AWS or GCP for running financial pricing models.
• Design and implement the orchestration layer to efficiently distribute millions of pricing tasks across hundreds of thousands of CPU/GPU cores.
• Deploy, manage, and version control quantitative pricing models in a distributed environment.
• Monitor and optimize cloud grid performance, cost, and resource utilization to drive continuous efficiency improvements.
• Collaborate with quantitative development teams to integrate new and updated pricing models into the production environment.
• Engineer data logistics to ensure market data, trade data, and model configurations are available for runtime calculations.
• Ensure the pricing engine remains highly available, resilient, and capable of meeting stringent recovery time objectives.
• **Only those lawfully authorized to work in the designated country associated with the position will be considered.**
• **Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client’s business needs and requirements.**
  
  

About Rose

• Founded in 1993
• Office Locations Across the U.S.
• 150+ Clients: Corporations and Government Agencies
• Employee Oriented Company
• Challenging Assignments Across the U.S.
• Continuous Professional Development
  
  

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