Quantitative Analyst – Commodities Investment Team (Summer Internship

Summer Intern, Commodities Quantitative Analyst

The BAM Commodities business is looking for summer interns to work on all facets of portfolio management directly with senior investors. The ideal candidate will have a quantitative background, experience coding in Python, and familiarity with Excel. Experience with commodities products is a plus. Strong interest in commodities is a must. This is a unique opportunity to work and learn in a dynamic team setting and get exposure to the various asset classes and products of Commodities.

The commodities quantitative analyst intern is expected to contribute meaningfully to portfolio management teams over the summer and learn quickly in a fast-paced environment. Example project work includes:

• Work on data analysis projects, prototyping and back-testing that directly influence trade idea generation
• Generate and implement ideas to improve existing strategies and optimize the current portfolio
• Help build market monitors and relative value reports to identify and track new trades
• Develop models on market-relevant topics, such as economic data, forecast prices, market products, supply/demand models, etc.

Rising junior undergrad or 1st year master's student in a quantitative field with a December 2027 or Spring 2028 graduation date. Bachelor's in computer science, finance, mathematics, or other STEM related fields. The internship is in Houston or Boston – must be willing to work in either location. There will be more positions available in Houston than Boston. Programming experience in Python in the context of data analysis, with the ability to test ideas and develop infrastructure for further research.

Understanding and exposure to options, derivatives, equity index futures, commodity futures, fixed income futures, interest rate swaps, supply and demand and foreign currencies. Knowledge of statistics, including time series and regression analysis. Strong organizational skills with the ability to present results clearly and iterate with PMs accordingly.