The role requires developing ML and quantitative systems using financial time series data, deploying models, and improving signal evaluation for investors.
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.
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.
- 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
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.
- 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
- Prior buy-side or sell-side experience
- Experience with alternative data
- 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
- 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
- Base salary: £110,000 to £200,000 depending on experience
- Equity included
- In-office role based in London
- No agency candidates
Salary Range
£110,000—£200,000 GBP
Toggle AI London, England Office
8-12 Broadwick St, London, United Kingdom, W1F 8HN
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