Quantitative Developer - Commodities Investment Team (Summer Internship)
The commodities developer internship places students with investment teams. Projects combine research tools, market analytics and software supporting portfolio decisions.
What you’d work on
Our reading of the posting: what a new hire in this role would most likely spend their first months on.
- Prototype and test data-driven trade ideas
- Build reusable components for systematic workflows
- Develop market monitors and relative-value reports
- Help model commodity supply and demand
What they ask for
Required
- Python or JavaScript for analysis
- Statistics and time-series methods
- Quantitative academic background
- Interest in commodities
- Clear presentation of research
Preferred
- Data engineering
- Distributed systems
- Cloud platforms
- Optimisation or machine learning
- Education
- Undergraduate or first-year master study in a quantitative subject; graduation in winter 2027 or spring 2028.
- Experience
- Student internship.
- Languages and tools
- Markets
- commodities
How to prepare
- Build a small commodity data monitor in Python
- Backtest a simple idea with documented data timing
- Explain a supply-demand model and its limitations
What to study
- Quantitative Data Engineering
- Python for Quantitative Finance
- Trading Systems and Low-Latency Infrastructure
The HFT Quant Developer roadmap sets out the stages for this kind of role, with free resources for each.
Open the roadmapApply
Read the full posting on Balyasny Asset Management’s site before applying: requirements, location and pay can change after we check them.
View the posting on Balyasny Asset Management’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Balyasny Asset Management and doesn’t handle applications.