Machine Learning Researcher - Intern

Point72 is recruiting for Machine Learning Researcher - Intern in New York. This listing was last seen on the firm's own job board on August 22, 2026.

A multi-manager fund whose academy programmes are the clearest structured entry route on the buy side.

What sets Point72 apart: Academy programmes that take candidates with no prior finance experience. Discretionary and systematic sides hire on different criteria. Cubist is the systematic arm and runs its own quant process.

Related preparation: Quantitative Researcher (QR) Career Roadmap, Machine Learning Quant Career Roadmap, Quant Strategist (Desk Quant) Career Roadmap, Quant Data Scientist (Alternative Data) Roadmap, Quant Research Ops (MLOps) Roadmap and Financial Data Scientist Career Roadmap.

The role, as Point72 describes it, published on August 15, 2024 and reproduced from their job board:

JOB DESCRIPTION

Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation.

Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior.

DESIRABLE CANDIDATES

Students enrolled in a PhD program in machine learning, computer science, statistics, or a related field.

Superb analytical and quantitative skills, along with a healthy streak of creativity.

Demonstrated ability to conduct independent research utilizing large data sets.

Passion for seeing research through from initial conception to eventual application.

Curiosity about financial markets

Strong scientific programming in Python, R or Matlab.

Empirical, detail-oriented mindset.