Summer Quant Trading Internship - AI, Data & Signals

P2P; New York (NY); On-site; USD 38,000 - 42,000; Part time

Benefits offered by this job

Housing stipend

Completion bonus

Job summary

Brevan Howard offers a Summer Internship Program for PhD candidates or 1st-year Master’s students who want to apply quantitative and ML skills to real-world problems in a fast-paced, feedback-driven environment. You will work with front-office teams to build data pipelines, develop models, trading signals, and AI-powered tools, and contribute to a core analytics library used across research, trading, and risk management.

A one-week in-depth training covers markets, AI, and Python.

Qualifications

• Strong mathematical and quantitative problem-solving abilities.
• Programming in Python.
• Interest in financial markets, trading, and financial products.
• Ability to work independently and in a team.
• Strong written and verbal English communication.

Responsibilities

• Build pipelines to extract and analyze data, develop models and trading signals, and support decision-making of Portfolio Managers.
• Integrate AI into analytical systems and build AI-powered tools using the latest LLMs and agent workflows.
• Contribute to the core analytics library used by Quants and PMs for research, trading and risk management.
• Participate in a one-week in-depth training on Financial Markets, including Macroeconomics, FX, Digital Assets, Derivatives, Equity, Bonds, and AI tools.
• During the program, support Portfolio Management teams on projects such as trading strategies, signals, backtesting, and market model development.
• Attend talks, mentorship, and social events; explore future paths in the Graduate Program.

Skills

Mathematics

Quantitative analysis

Python programming

English communication

Teamwork

Entrepreneurial spirit

Education

PhD candidate

Master's student

Tools

Excel

VBA

R

Job description

Brevan Howard offers a Summer Internship Program for PhD candidates or 1st-year Master’s students who want to apply quantitative and ML skills to real-world problems in a fast-paced, feedback-driven environment. You will work with front-office teams to build data pipelines, develop models, trading signals, and AI-powered tools, and contribute to a core analytics library used across research, trading, and risk management.

A one-week in-depth training covers markets, AI, and Python.