Quant jobs / Balyasny Asset Management

Senior Data Scientist - Equities

The equities data-science team supports technology, media and telecom investment research. This scientist builds forecasts, data products and AI workflows alongside portfolio managers.

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.

Frame TMT investment debates as empirical research questions
Build forecasts from sector and alternative datasets
Develop AI-assisted research workflows
Scale data products and explain their investment relevance

What they ask for

Required

Seven or more years of data science or analytics
Statistics and machine learning
TMT sector datasets
Python and SQL
LLM application experience
Communicating to investors

Preferred

Equities investing
Software-design knowledge

Education: Bachelor or master qualification in a quantitative, computing, economics or technology subject.
Experience: 7+ years in data science, analytics or a related discipline.
Languages and tools: Python
SQL
Snowflake
Git
Linux
Markets: equities

How to prepare

Present a sector research case with measurable predictive evidence
Show how alternative-data preparation affects a forecast
Evaluate an AI research workflow against verified conclusions

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.