Quant Developer

Description On-site in Jersey City, NJ

Our client seeks a senior software engineer to lead design and development of next-generation electronic trading systems and data infrastructure. The role requires hands-on leadership building scalable, resilient, and high-performance platforms for capital markets, with emphasis on KDB+/q, Python, and AI/ML applied to time-series data. You will collaborate across quant, product, and engineering teams, mentor peers, and deliver robust production systems that support research, backtesting, and real-time trading workflows.

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $80.00 to $90.00/hr. w2

JN -052026-107108

Responsibilities

• Lead design and development of low-latency, high-throughput trading systems and workflows.
• Design, develop, and optimize KDB+/q databases and analytics for high-volume market data.
• Develop Python-based AI and quantitative models for research, prediction, classification, and signal generation.
• Apply machine learning techniques to time-series data including feature engineering, model training, and evaluation.
• Build research and backtesting frameworks integrating AI models with historical data.
• Translate quantitative and ML research into production-ready, resilient systems.
• Integrate AI models into real-time and batch pipelines.
• Optimize analytics and model evaluation for performance, stability, and scalability.
• Collaborate with quants, product owners, and engineering on deployment and monitoring.
• Support production systems and participate in on-call rotations, including occasional weekend support.

Experience Requirements

• 10+ years of professional experience in quantitative finance or trading systems.
• Advanced proficiency with KDB+/q for time-series modeling, high-performance querying, and real-time and historical analytics.
• Strong Python for quantitative analysis, AI/ML model development, and integration with KDB+ and downstream systems.
• Experience with large-scale, high-frequency, or noisy datasets.
• Solid software engineering practices including Git, testing, and modular design.
• Experience with AI developer assist tools such as GitHub Copilot.
• Experience with CI/CD tools such as GitHub, Maven, Jenkins, Artifactory, and uDeploy.
• Hands-on experience with AWS or other cloud platforms.
• Familiarity with Java or other object-oriented languages.
• Experience with Linux, shell scripting, and production support.
• Clear communication with quants, traders, and engineers.

Education Requirements

• Bachelor’s degree in Mathematics, Computer Science, Engineering, Information Technology, or equivalent.