Quant jobs / Polymer Capital Hong Kong

Data Specialist (Analyst, Risk & Quant Analytics)

Polymer’s research-data specialist evaluates and onboards datasets for investment teams. The role checks whether information is timely, usable and appropriate for quantitative research.

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.

Assess market and alternative dataset quality
Check historical depth and point-in-time availability
Run vendor proof-of-concept evaluations
Coordinate integration and maintain data documentation

What they ask for

Required

One to three years of relevant data work
Financial and alternative-data familiarity
Python and SQL basics
Dataset quality assessment
Database/API familiarity
Communication with researchers and vendors

Preferred

Investment-firm experience
Financial-data platforms
Research-data bias concepts

Education: Bachelor study in finance, financial engineering, computing, data science or a related area.
Experience: 1–3 years in data analysis, data operations or research support.
Languages and tools: Python
SQL
Markets: multi-asset

How to prepare

Profile a candidate dataset for research usefulness
Demonstrate checks for survivorship and timing bias
Document delivery, schema and data-quality requirements

What to study

The HFT Quant Developer roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

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.