Machine Learning and Quant Engineer - London

You think in time series, signals, and regimes.
You care about insight quality, not academic purity.
You want your models tested by markets, not papers.
If you dislike messy data and real-world constraints, this is not your role.

The Role, In Plain English

You will build quantitative and ML-driven insight systems using structured time series data.
This role exists to turn raw financial data into actionable investor signals.
You will work closely with engineers to productionize quant logic.

What You’ll Be Responsible For

• Develop models using structured financial time series


• Build insight generation and scenario analysis pipelines


• Collaborate with backend engineers to deploy models in production


• Evaluate signals based on real investor outcomes


• Improve attribution and explainability

What “Good” Looks Like in This Role

After 3 months:
Shipping signals used internally.

After 6 months:
Signals used by customers.

After 12 months:
You shape how quant insights are built at Reflexivity.

Who You Are (Must-Haves)

• 5 plus years experience in quant, ML, or financial modeling


• Strong Python skills


• Startup experience on core systems


• Investment domain knowledge


• AI-assisted coding experience

Nice-to-Haves (Not Deal Breakers)

• Prior buy-side or sell-side experience


• Experience with alternative data

How We Work

• In-office team with high trust and high ownership


• Direct communication, minimal process, strong opinions backed by data


• Engineers are expected to think about product impact, not just code


• We move fast when it matters and slow down when correctness matters more

Why This Role Is Worth Your Time

• Direct influence on how professional investors make decisions


• Hard problems at the edge of AI, data, and finance


• Real ownership and technical autonomy


• Senior peers who care about quality and outcomes

Compensation & Practicalities

• Base salary: £110,000 to £200,000 depending on experience


• Equity included


• In-office role based in London


• No agency candidates