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# Python Quantitative Developer

- **Company:** Axelon Services Corporation
- **Location:** Jersey City, NJ, United States
- **Experience:** Expert
- **Salary:** $189,280.0 - $199,680.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Computer Programming, Software Debugging, Distributed Systems, Job Scheduling, Python (Programming Language), Performance Tuning, HybridCloud, Event Driven Architecture, Containerization, Kubernetes, Information Technology, Docker
- **Published:** November 3, 2026
- **Apply:** https://www.thejobnetwork.com/job/e9c4635a-d9f5-40c4-a288-8818172f550e/python-quantitative-developer

## About the Role

* Minimum 10 years of professional experience with a proven track record of designing and building applications for massive-scale, high-performance compute 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 on large-scale grids.
 * Deep expertise in building event-driven architectures and handling asynchronous notifications and replies from distributed systems.
 * 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.
 * Proven ability to debug complex pricing and model-related issues by partnering directly with quantitative analysts.
 * Prior experience in a similar role within the financial industry, specifically working on quantitative pricing platforms, large-scale risk calculations, or XVA grids.

## Description

* 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.