Quant jobs / Balyasny Asset Management

Data Scientist, Enterprise Data Technology

Enterprise Data Technology supplies investment teams with reliable research datasets. This data scientist combines analytical investigation with data-product ownership and automated quality controls.

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.

Assess vendor data for coverage and timing problems
Automate checks for outliers, missing values and schema changes
Onboard and document research datasets
Prioritise data-product improvements with investment users

What they ask for

Required

Python and SQL
Large-dataset analysis
Financial reference or market-data knowledge
Data-quality investigation
Independent problem-solving
Clear stakeholder communication

Education: No degree requirement is specified.
Experience: Experience in data science, engineering, analytics or another quantitative field.
Languages and tools: Python
SQL

How to prepare

Profile a vendor dataset and document suitability for research
Build quality checks for identifier and schema changes
Explain how a data defect could affect an investment analysis

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.