Quant jobs / DRW

Quantitative Researcher – Equities

A researcher on a mid-frequency equity statistical arbitrage team, working with the portfolio manager across the whole research pipeline. It runs from data processing to live deployment.

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.

Design predictive signals and features across global equities
Build point-in-time data cleaning and feature pipelines
Help build backtesting and research infrastructure
Create tools for performance attribution and live monitoring

What they ask for

Required

2–8 years in quant equities focused on alpha research
Standard and alternative equity datasets
Point-in-time data handling and ticker mapping
Strong Python
SQL and distributed data environments

Education: PhD or MSc in maths, physics, statistics, computer science or a related quantitative subject
Experience: 2–8 years in quant equities alpha research
Languages and tools: Python
SQL
Markets: equities

How to prepare

Build a cross-sectional equity signal using point-in-time fundamentals and test it properly
Learn the data pitfalls: survivorship bias, lookahead, corporate actions, identifier changes
Practise SQL and larger-than-memory data handling
Study statistical arbitrage and factor-neutral portfolio construction

What to study

The Quantitative 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 DRW’s site before applying: requirements, location and pay can change after we check them.

View the posting on DRW’s site ↗

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