# Research Scientist, Causal Inference

**Company**: Relay
**Location**: London, Greater London
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Data Science
**Industry**: Technology

**Apply**: https://jobs.ashbyhq.com/relay/6ab34294-e9e3-4057-a809-4980fe5d28e8?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/research-scientist-causal-inference-72d1932d-a7c/

## Description

Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M) led by deep-tech investors Plural, and a recently closed Series B ($95M), Relay is scaling faster than 99% of venture-backed startups.

As a Research Scientist at Relay, you'll lead causal inference at Relay from the start. You'll set the standard for causal inference, measure how Relay's decisions affect each courier, shape how Relay experiments across a live, two-sided marketplace, adapt advanced techniques across causal inference, statistics, and machine learning to Relay's problems, and partner with Operational Research to embed your insights and models into Relay's network-wide optimisation.

Responsibilities:

- Set the standard for causal inference at Relay.

- Measure how Relay's decisions affect each courier, today and over time.

- Shape how Relay experiments across a live, two-sided marketplace.

- Adapt advanced techniques across causal inference, statistics, and machine learning to Relay's problems, and see them through to production.

- Partner with Operational Research to embed your insights and models into Relay's network-wide optimisation, and help build Relay's research culture and voice in the tech community.

Requirements:

- Deep expertise in causal inference, experimentation, and machine learning.

- Experience applying advanced techniques to real marketplaces or products.

- Strong technical fundamentals and entrepreneurial drive.

Benefits: No specific benefits mentioned.

Who Thrives at Relay?

- Aim with Precision: Define problems clearly and measure impact meticulously.

- Play to Win: Chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction.

- 1% Better Every Day: Believe that small, consistent improvements lead to exponential growth.

- All In, All the Time: Show up and step up, take ownership from start to finish, and do what it takes to deliver when it counts.

- People-Powered Greatness: Invest in teammates, give and receive feedback with care and candour, and build trust through high standards and shared success.

- Grow the Whole Pie: Seek out win-win solutions for merchants, couriers, and customers.

For more fresh new jobs, check out [yubhub.co](https://yubhub.co/).

## Skills

### Required
- causal inference
- experimentation
- machine learning
- statistics
- operational research

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Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/relay/6ab34294-e9e3-4057-a809-4980fe5d28e8?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)