Quant jobs / Qube Research & Technologies

Data Scientist – Options

A data role in Data Search & Analytics, attached to one of the firm's options trading streams. You provide the datasets behind systematic options 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.

Source and onboard options and volatility datasets
Build pipelines that keep options data timely and consistent
Turn researcher and trader data requests into reusable tooling
Improve coverage and quality of the internal options data platform

What they ask for

Required

Python with Pandas and NumPy
Data pipelines
Large structured time-series data
Financial market data experience
Interest in markets and quantitative trading
Stakeholder communication

Preferred

Options, derivatives or volatility data exposure
Experience supporting quant research or trading teams

Education: No degree level stated.
Experience: 3+ years as a data scientist, data engineer or similar
Languages and tools: Python
Pandas
NumPy
Markets: options

How to prepare

Learn the structure of an options chain and what makes the data messy
Build a pipeline that cleans options quotes and computes implied volatility
Study volatility surfaces and how bad data distorts them
Practise handling large time-series with efficient storage formats

What to study

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

Open the roadmap

Apply

Read the full posting on Qube Research & Technologies’s site before applying: requirements, location and pay can change after we check them.

View the posting on Qube Research & Technologies’s site ↗

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