Quant jobs / Balyasny Asset Management

Data Scientist - Geospatial and Remote Sensing (Summer Internship - Master's)

The geospatial internship researches alternative information for commodity investment decisions. Projects can use imagery, mobility, weather or crop data and carry models through to usable analytical outputs.

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.

Prepare satellite or other spatial datasets
Fit and validate models for commodity-related questions
Build data pipelines and cloud-based analytical outputs
Explain findings and limitations to investment professionals

What they ask for

Required

Python and SQL
Statistical and machine-learning methods
Large-dataset processing
ETL and Git familiarity
Analytical communication

Preferred

Alternative-data work
PostGIS/STAC
Cloud platforms
Deep-learning tools

Education: Master student in a quantitative, computing or geospatial subject, graduating December 2027–May 2028.
Experience: Ten-week student internship.
Languages and tools: Python
SQL
NumPy
pandas
scikit-learn
matplotlib
Markets: commodities

How to prepare

Build a spatial-data workflow with documented coordinate and timing assumptions
Evaluate a weather or crop prediction using historical holdouts
Create a concise visual explanation of model errors

What to study

The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

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.