Top Tech Jobs & Startup Jobs in NYC, NY

11-week software engineering internship building high-performance, large-data research platforms and trading tools. Work in small teams on system architectures, distributed systems, NLP and ML, and web frameworks while collaborating with senior engineers.

Develop and improve mathematical models for trading strategies, conduct research and statistical analysis in a fast-paced team environment.

Early-career data scientist supporting sector investment teams: deliver data pulls, analyses, trackers, dashboards, anomaly investigations, and reusable Python/SQL tooling. Use time-series methods, alternative data, and LLMs to accelerate workflows and build commercial judgment with investors.

Summer 2027 internship supporting Sector Data Scientist and investment teams by acquiring, cleaning, and analyzing multiple data sources, testing investment hypotheses, identifying key data drivers and inflection points, and presenting research and decision-support tools to inform investment decisions.

The Recruiting Coordinator collaborates with recruiters to manage the hiring process, schedule interviews, and maintain candidate pipelines, requiring strong communication and organizational skills.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

As a Quantitative Research Engineer, design, develop, and implement software for automated trading systems using advanced statistical techniques. Collaborate with researchers and prioritize business needs.

As a PhD intern, you will design and develop software solutions for automated trading systems, collaborating closely with the Quantitative Research team.

As a Quantitative Researcher Intern, you'll develop models and strategies, conduct statistical analysis, and implement algorithms in a trading context.

Develop high-performance research platforms and tools that bring trading strategies to life. Work in small teams to design, build, and deploy resilient systems using distributed computing, NLP, and machine learning to solve large-data problems in finance.