Staff Applied Scientist, Causal Inference — Live Marketplace

Relay; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Relay is building the future of logistics in a data-driven online era. As Staff Applied Scientist, you will set the standard for causal inference, measure the impact of decisions on couriers over time, and shape experiments across a live two-sided marketplace.

You will adapt advanced causal inference, statistics and ML techniques to real-world problems, productionize models, and collaborate with Operations Research to optimise network-wide performance.

Qualifications

• Bring deep expertise in causal inference, experimentation and ML, from PhD, publications, or frontier industry work.
• Experience applying advanced techniques to real marketplaces or products and owning outcomes.
• Ability to think in mechanisms and let evidence guide decisions.

Responsibilities

• Set the standard for causal inference at Relay.
• Measure how decisions affect each courier, today and over time.
• Shape how the company experiments across a live, two-sided marketplace.
• Adapt advanced techniques across causal inference, statistics and ML to company problems and see them through to production.
• Partner with Operational Research to embed insights into network-wide optimisation and contribute to the research culture.

Skills

Causal inference

Experimentation

Machine learning

Statistics

Communication

Education

PhD or publications

Tools

Operational Research

Production ML systems

Job description

Relay is building the future of logistics in a data-driven online era. As Staff Applied Scientist, you will set the standard for causal inference, measure the impact of decisions on couriers over time, and shape experiments across a live two-sided marketplace.

You will adapt advanced causal inference, statistics and ML techniques to real-world problems, productionize models, and collaborate with Operations Research to optimise network-wide performance.