Quant jobs / Point72

Microstructure Quantitative Researcher

A research role in a quantitative portfolio management team at Point72 that builds systematic macro strategies using market microstructure signals. The work centres on order book tick data over intraday to daily horizons.

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.

Engineer features from order book tick data
Build microstructure-based signals for futures and FX
Combine features with linear and machine-learning models
Backtest, implement and maintain strategies in production

What they ask for

Required

MS or PhD in a quantitative field with a strong statistics foundation
4+ years of intraday-to-daily statistical modelling for trading
Futures or FX market microstructure knowledge
Tick-data feature generation and modelling
Python, R or C/C++
scikit-learn and pandas

Education: MS or PhD in physics, engineering, statistics, applied maths, quantitative finance or similar
Experience: 4+ years of quantitative research on intraday-to-daily trading strategies at a successful proprietary trading team
Languages and tools: Python
R
C/C++
Markets: futures, fx

How to prepare

Build features such as order imbalance and queue dynamics from public tick or L2 data
Study how limit order books work and the main microstructure models
Practise handling very large tick datasets efficiently
Learn how to evaluate signals net of spread and impact

What to study

The HFT 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 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.