Python Developer w/ Quant

Job Description

Job Description

Location:  within 50 miles of Jersey City, NJ - 3 days on site mandatory in a week

Pay Range: $70-$75/Hr.

Applicants must be able to work directly for Artech on W2 from Day 1

 

Introduction

Are you interested in building the next-generation risk quant pricing platform that runs on large-scale, high-performance compute grids? Are you driven by the challenge of orchestrating trillions of calculations across a hybrid cloud environment to compute risk P&Ls with extreme speed and precision? Do you want to own the core platform that brings sophisticated front-office pricing models to life at an industrial scale? The client is seeking a visionary Lead Engineer to architect and build our global Quant Pricing Platform. This is the computational heart of our risk system, where complex quantitative models meet massive-scale infrastructure. You will be responsible for creating a seamless, high-performance ecosystem that spans both in-house and external cloud grids, delivering the computational power our quants need to manage risk effectively.

Required Skills & Qualifications

• 10 years of professional experience with a proven track record of designing and building applications for massive-scale, high-performance compute (HPC) grids.
• A degree in a highly technical field such as Computer Science or Quantitative Finance.
• Deep domain knowledge in Capital Markets, financial derivatives, and a strong understanding of financial regulations like FRTB.
• Expert-level experience with job scheduling, resource management, and workload optimization techniques (task packing, prioritization) on large-scale grids.
• Deep expertise in building event-driven architectures and handling asynchronous notifications and replies from distributed systems.
• Prior work experience at client or in client's Industry
• Applicants must be able to work directly for Artech on W2

Preferred Skills & Qualifications

• Proven experience designing and building intelligent monitoring tools, ideally leveraging ML for anomaly detection and performance tuning.
• Expert-level experience managing workloads in a hybrid cloud environment, with deep knowledge of at least one major public cloud (AWS, GCP) and on-premise grid technologies.
• Deep expertise in containerization, orchestration, and scheduling technologies (Docker, Kubernetes).
• Strong programming skills in languages common to high-performance and quantitative computing, such as C and Python.

Day-to-Day Responsibilities

• Architect and build a next-generation, hybrid-cloud platform for running quantitative pricing calculations at massive scale.
• Design a sophisticated job orchestration and scheduling system that handles dynamic prioritization, efficient task packing, and resource optimization across the grid.
• Engineer a robust, event-driven framework for managing the entire job lifecycle, including handling notifications for job completion and managing the flow of result data from the grid.
• Develop a comprehensive error-handling and resiliency strategy to gracefully manage failures in a large-scale distributed environment.
• Pioneer the development of an intelligent monitoring platform using ML to perform anomaly detection, predict job failures, and optimize grid performance.
• Engineer the secure and efficient data logistics required to move terabytes of market and trade data between on-premise systems and public cloud environments.
• Partner closely with front-office quants to onboard, version, and optimize their C and Python pricing models for distributed computation.

For immediate consideration please click APPLY or contact me directly at View email address on ziprecruiter.com