Data Scientist, Risk & Quant Analytics
Polymer’s risk and quant analytics scientist researches signals from market, position and alternative data. The role develops statistical forecasts and tests their value for trading and risk decisions.
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.
- Prepare market and alternative datasets
- Model security, sector or alpha rankings
- Test hypotheses and evaluate predictive robustness
- Explain model findings to different investment audiences
What they ask for
Required
- Quantitative postgraduate study
- Statistics and probability
- Python or R
- Dataframe processing
- Machine-learning tools
- Analytical communication
Preferred
- Market microstructure
- Behavioural finance
- Education
- Master or higher qualification in data science, statistics, maths, computing or a related field.
- Experience
- Relevant technical capability is required; no minimum year count is published.
- Languages and tools
- Markets
- equities, multi-asset
How to prepare
- Build an out-of-sample ranking experiment
- Explain how position and alternative data are aligned in time
- Compare a model against simple statistical benchmarks
What to study
- Probability, Statistics and Financial Data
- Quantitative Research, Data and Backtesting
- Financial Machine Learning
The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.
Open the roadmapApply
Read the full posting on Polymer Capital Hong Kong’s site before applying: requirements, location and pay can change after we check them.
View the posting on Polymer Capital Hong Kong’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Polymer Capital Hong Kong and doesn’t handle applications.