Top Tech Jobs & Startup Jobs in NYC, NY

Identify, evaluate, and source datasets for quantitative research and financial markets. Manage the data lifecycle, vendor relationships, repository, and cross-functional delivery with Legal, Compliance, Engineering, and Procurement. Drive data projects, communicate recommendations, attend industry events, and help shape the firm’s long-term data strategy.

Finance Associate supporting treasury, finance, fund reporting, tax compliance, cash management, margin analysis, and counterparty management. The role rotates across FACT functions, improves workflows using data and AI tools, collaborates with internal technical and operational teams, liaises with external providers, and contributes to special projects and ad hoc analyses. This is a hybrid position requiring at least three days weekly in the New York City office.

Conduct quantitative research with senior researchers on trading strategies and models. Develop statistical models, investigate signals, optimize strategies, and analyze large-scale datasets using advanced computational resources. Collaborate in a rigorous academic environment, present complex ideas, and solve challenging real-world problems.

Designs, implements, and operates cloud-based HPC platforms supporting quantitative research and trading. Responsibilities include cloud architecture, HPC scheduling, containerization, software distribution, automation, CI/CD, monitoring, capacity management, benchmark optimization, and production support. Partners with researchers and engineers to deliver reliable, scalable, high-performance computing systems.

As a Quantitative Researcher, you'll create and improve trading models while collaborating with senior researchers and conducting your own research.

Software Engineers at PDT develop and maintain trading systems, risk controls, and post-trade technologies while collaborating with users to meet requirements.

The Trading Operations Analyst monitors trading activities, ensures compliance with trading limits, analyzes market events, and develops internal tools and automation.

The Research Engineer will develop scalable infrastructure for machine learning research, optimize workflows, and enhance model inference for trading systems.

The Applied ML Scientist will collaborate with researchers to develop and improve statistical methods that enhance trading strategies through applied machine learning.

Performance Engineers are responsible for understanding and optimizing systems for trading strategies, focusing on efficiency, cost reduction, and scaling models. They analyze system performance across software and hardware layers, implement improvements, and conduct evaluations to enhance throughput and resource utilization.