Quantitative Developer

Dex; Greater London; On-site; GBP 450,000 - 550,000; Full time

Job summary

Dex in London seeks an ML / Quant Research Engineer to join top quantitative teams. You'll tackle signal generation, execution and production ML on financial data, with ownership and rigorous validation.

You will work with quants, traders and engineers to push ideas from concept to production, using Python/SQL and strong statistical foundations.

Qualifications

• Strong ML or quantitative research background, with production experience.
• Deep statistical fundamentals: regression, time-series, hypothesis testing.
• Strong Python and SQL, plus comfort going lower-level when required.
• Track record of high-quality work in technically rigorous environments.

Responsibilities

• Working on signal generation, execution and production ML against financial data.
• Building and deploying production ML systems on financial data.
• Running rigorous experimentation against meaningful baselines.
• Partnering with quants, traders, and engineers across the firm.

Skills

Machine Learning

Quantitative research

Production experience

Python

SQL

Statistics

Tools

Python

SQL

Job description

ML / Quant Research Engineer (Top Quantitative Firms | £500k+)

Location: London

The top quantitative trading and research teams are always searching for great engineers, and the bar to get in is high. We work closely with a number of them, so we know what they actually hire for and what the work is like day to day. Expect high agency and real ownership, with teams who understand that a great hire isn't only about your stack — your ambition, potential and motivation matter just as much.

The opportunities

Salaries can hit £500k+, and the problems earn it. You'd be working on signal generation, execution and production ML against financial data, where a good idea shows up in the results almost straight away and rigour is non-negotiable. The compute is serious and the people around you are among the sharpest in the field.

You could work on

• Applying ML and statistical methods to time-series, signal generation, or execution problems
• Building and deploying production ML systems on financial data
• Running rigorous experimentation against meaningful baselines
• Partnering with quants, traders, and engineers across the firm

You may have

• Strong ML or quantitative research background, with production experience
• Deep statistical fundamentals: regression, time-series, hypothesis testing
• Strong Python and SQL, plus comfort going lower-level when required
• Track record of high-quality work in technically rigorous environments

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