Quant jobs / Point72

Data Scientist – Cubist Data Services

A data role in Cubist's Data Services group, which supplies clean, reliable data to systematic portfolio managers. It underpins both research and live trading of large amounts of capital.

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.

Onboard new external datasets into the firm's research platform
Write and deploy data pipelines that reshape, aggregate and engineer features from raw data
Set up automated alerts and reports that flag data-quality problems
Talk to vendors and portfolio managers to understand each dataset and what the researchers need from it
Run quick preliminary analyses to share with investment teams

What they ask for

Required

Master's in financial engineering, statistics, computer science or similar
Strong Python
Strong SQL
Care about data quality and process
Clear written and spoken communication
Prioritising several tasks at once

Preferred

AWS
Linux
Airflow
Finance industry experience

Education: Master's in financial engineering, statistics, computer science or another rigorous quantitative field
Experience: No fixed years stated; finance experience a plus
Languages and tools: Python
SQL
Markets: equities, futures, options

How to prepare

Build a pipeline that pulls a public dataset, cleans it, tests it and schedules it, ideally with Airflow
Practise advanced SQL, including window functions and joins on large tables
Learn the common data problems in market data, such as survivorship bias, corporate actions and timestamps
Get comfortable with the Linux command line and basic AWS services

What to study

Apply

Read the full posting on Point72’s site before applying: requirements, location and pay can change after we check them.

View the posting on Point72’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Point72 and doesn’t handle applications.