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 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. #J-18808-Ljbffr