2026 BSc/MSc/PhD Quantitative Research/Strat Internship

Schonfeld is recruiting for 2026 BSc/MSc/PhD Quantitative Research/Strat Internship in São Paulo, Brazil. This listing was last seen on the firm's own job board on August 22, 2026.

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 Schonfeld describes it, published on May 21, 2026 and reproduced from their job board:

The Role

We are seeking exceptional MSc or PhD candidates to join our Quantitative Research and strat teams in Sao Paulo where they will work with other researchers and developers on various research projects, including the design of novel predictive signals, enhancement of our algorithms for prediction, trade execution, portfolio construction, risk management, product and asset modelling. Interns will have an opportunity to meaningfully contribute to all facets of a successful quantitative trading business; help it grow and diversify.

What you’ll do

Depending on the portfolio manager team you join, as a Quantitative Researcher/strat Intern you will be directly responsible for furthering our platform build and/or alpha research. You will understand the economics of a fundamental domain, and the corresponding insights that can be gathered from associated alternative data offerings. You will identify compelling differentiating factors, design novel predictive signals, backtest & validate hypotheses. You will have the opportunity to collaborate with senior team members to learn what it takes to be a successful quantitative strat + researcher.

What you need:

Current BSc, MSc PhD student in a quantitative or technical field such as statistics, economics, mathematics, physics, electrical engineering, or computer science (ideally with one or two years left in your academic program)

Excellent programming skills in languages such as Python, C, C++, Java, SQL, or R

Strong knowledge of probability and statistics (e.g., machine learning, time-series analysis and forecasting, pattern recognition, NLP, and unstructured data analysis).

The ability to communicate research ideas clearly and succinctly

Creative problem-solving skills and experience working with real-world datasets

Strong attention to detail

Please submit your CV/resume in English

We’d love if you had: