Quant jobs / WorldQuant

Quantitative Execution Strategist

An execution researcher role refining WorldQuant's execution across cash and derivative products in APAC. It covers algorithms, market impact modelling and transaction cost analysis.

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.

Specify and implement new and improved execution algorithms in Python
Build market impact models from large datasets
Run transaction cost analysis and feed results to PMs and traders
Build reusable Python tools for the team

What they ask for

Required

PhD or Master's in a quantitative field
0-4 years in quant research or development
Solid Python
Data structures and algorithms
SQL on large datasets
Regression, time series and applied machine learning

Preferred

C/C++
Deep learning or reinforcement learning

Education: PhD or Master's in CS, maths, statistics, physics, engineering or quant finance
Experience: 0-4 years in quantitative research or development for systematic or execution strategies
Languages and tools: Python
C++
SQL
Markets: equities, futures

How to prepare

Fit a square-root market impact model on public trade data
Study optimal execution, such as Almgren-Chriss
Run a TCA study comparing execution benchmarks
Practise regression and ML on high-frequency data

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

View the posting on WorldQuant’s site ↗

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