Lead Causal Inference Scientist — Production ML

Relay Technologies; Greater London; Hybrid; GBP 140,000 - 190,000; Full time

Job summary

Relay Technologies is seeking a Staff Applied Scientist to lead causal inference initiatives across a live two-sided marketplace. You will measure effects on couriers over time and shape experiments, applying advanced ML and statistics to production systems.

Ideal candidates bring PhD-level or equivalent experience, a track record in causal inference and production-ready tooling, and a collaborative mindset to grow Relay's research culture.

Qualifications

• PhD or equivalent in a quantitative field with a publication record or industry impact.
• Proven track record in causal inference, experimentation, and ML in production.
• Experience applying advanced methods to live marketplaces or products.

Responsibilities

• Set the standard for causal inference at Relay.
• Measure how decisions affect couriers today and over time.
• Shape experimentation across a live two-sided marketplace.
• Advance techniques in causal inference, statistics and ML to production.
• Embed insights into Relay's network-wide optimisation and research culture.

Skills

Causal inference

Experimentation

Machine learning

Statistics

Communication

Collaboration

Problem solving

Education

PhD or equivalent

Quantitative background

Tools

Python

SQL

Experimentation tooling

Job description

Relay Technologies is seeking a Staff Applied Scientist to lead causal inference initiatives across a live two-sided marketplace. You will measure effects on couriers over time and shape experiments, applying advanced ML and statistics to production systems.

Ideal candidates bring PhD-level or equivalent experience, a track record in causal inference and production-ready tooling, and a collaborative mindset to grow Relay's research culture.