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DATA SCIENCE AT DELIVEROO

We’re the EMEA Data Science team.

We use data, experimentation and business knowledge to solve the complex challenges behind local commerce. We work throughout the company in product, operations, and platform teams, and shape decisions to improve experiences for millions of consumers, merchants, and delivery partners all around the world. We are great communicators, and move fast.

 

Two Deliveroo employees sitting on a sofa talking

Part of DoorDash, our EMEA Data Science team brings together Data Scientists and Analytics Engineers from across Deliveroo and Wolt.

Our mission is to drive the highest quality decision-making across our marketplace. Some work in central platform teams, while others are embedded directly within product or operations squads. Together, we build data products, run experiments, uncover opportunities, and drive decisions to improve experiences for consumers, merchants and delivery partners across our three brands.

Roles we hire for

1

Analytics Engineer

What you’ll work on
Build and maintain clean, tested and well-modelled datasets and context layers that power data products that work at scale.

Who you’ll work with
Partner directly with the business, Data Scientists and Product Engineers to make sure source data meets downstream needs, and that analytical models are robust, intuitive and easy to use.

The impact you’ll have
Make trusted data and consistent metrics easier to discover and use, enabling teams across the business to make better, faster decisions.

2

Data Scientist

What you’ll work on
Own analytical problems end to end, turning broad, ambiguous questions into structured approaches using experimentation, causal inference and analysis.

Who you’ll work with
Work within Product, Operations and Platform teams, partnering with technical and non-technical stakeholders across the business.

The impact you’ll have
Turn evidence into clear recommendations that influence roadmaps, improve our three-sided marketplace and raise the quality of decision-making.

  

Latest Roles

London, United Kingdom

Senior Data Science Manager

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London, United Kingdom - Deliveroo

Machine Learning Engineering Manager – Personalisation

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London, England

Senior Machine Learning Engineer – Recommendations

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Where Data Science Makes an Impact

Delivery

Predict demand, improve delivery-time estimates and optimise how orders and delivery partners are matched.

This team owns the algorithms and models which make our delivery network tick by connecting riders with orders, in real-time and in all our markets around the world. They also build and maintain our world-class rider app so riders can choose to log in to work and deliver orders quickly, safely and with ease whenever they want.

Consumer

Use experimentation and personalisation to improve discovery and help consumers make confident choices.

Helps consumers find and discover food that matters to them and feel confident in their choice. They are responsible for the in-app and web experience as well as customer acquisition and retention.

Grocery

Solve challenges across catalogue quality, inventory, substitutions and the online shopping experience.

Provides the technology and services for Grocery partners to be successful on the platform and includes: Partner Experience, Grocery Shopping Experience, Catalogue & Inventory, and Integrations.

Restaurants

Help merchants understand performance, reach new customers and grow through data-led products and insights.

Provides the technology and services that support restaurant partners to grow and thrive and includes: onboarding, restaurant operations, restaurant management, advertising, and support.

Watch our team in action

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Igor Khomyanin: Holdout Experiments; Patterns, Trade offs, and Lessons from Real Projects

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Ella Johnson-Watts: High quality experimentation at Deliveroo; The vision, implementation and reflection

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Mahana Mansfield: The Qualities That Great Data Scientists Share – and How to Assess Them

Building a world-class data org | Jessica Lachs (VP of Analytics and Data Science at DoorDash)

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Explore our thinking

  • Data Science

Experimentation Principles at Deliveroo

  • Leadership

Starting an Analytics Org From Scratch

  • Analytics Engineering

Analytics Engineering at Wolt

  • Smarter targeting

How DoorDash’s brand affinity powers smarter targeting

  • Re-joining Deliveroo

Like many others, I’ve just re-joined Deliveroo. Here’s why.

  • An insight into Jessica's world

Jessica Lach's Blog

  • Roonomics

Roonomics: How Economics Helped Us to Build a Churn Prediction Model

  • Automated governance

Unlocking AI innovation through automated governance

  • Machine learning

Deliveroo's Machine Learning Platform: Powering the Future of ML

  • First few months

My first few months as a data scientist at Deliveroo

  • Analytics Engineering

The Emergence and Evolution of Analytics Engineering at Deliveroo

  • Metrics

Metrics matter - how we set OKRs at Deliveroo

  • Experimentation

How to Experiment Rapidly Without Losing Rigour

Learning from each other

Our Data Science teams learn from each other’s work, in regular sessions across the team and in a wider community of economists.

Data Science Learning Fortnightly

Our EMEA Data Science team works as one, bringing together data scientists across Deliveroo and Wolt markets in London, Berlin, Helsinki, Stockholm and beyond. Every two weeks we get together to learn from each other’s work

A Data Science lead hosts each session, and the people presenting are the ones who did the work. They walk through an analysis, a new method or a tool they’ve built, so everyone else can pick it up and use it.

Sessions mix three things:

  • Great analysis and how we approach it. Experiment design, causal inference, sizing opportunities, or a deep dive into how one part of the business works.
  • Using AI well. From agents that review and check analysis to tools that let partner teams answer their own questions safely, with the rigour a data scientist would apply.
  • Getting the most from our experimentation platform. Our central Decision Science team shares new features and best practices, so we can run better tests and make decisions with confidence.

Recent sessions have covered:

  • A shared library that makes experiment planning and analysis faster and more consistent
  • An AI toolkit that lets operations teams run their own metric analysis, with every number backed by tested code rather than the model’s guesswork
  • How our teams set up specialised AI agents for planning, building and reviewing analytical work

Anyone can suggest a topic, and it’s a low-pressure way to practise presenting to a wider audience. Joining the team means learning from colleagues across two brands and many markets, and sharing your own work with them too.

Economics seminars and NABE TEC

Deliveroo’s Data Science org is home to a thriving community of economists and econometricians.

Each month we run a seminar series open to anyone interested in economics and related topics, where one of us presents a paper, a broader topic or current work. We also co-organise the European arm of the NABE TEC conference, which brings together economists working in tech companies across Europe. We’ll be hosting the 2028 edition at our London office.

Shaping how analytics works with AI.

We get access to the latest AI tools, and the internal infrastructure to use them well at scale. AI is part of our everyday work, not a side project.We’re also working out how AI changes analytics itself, on problems nobody has reliably solved yet:
  • Running long-running analytics agents with the right level of human supervision
  • Verifying AI-assisted analysis efficiently and rigorously
  • Storing experiments, past analyses and data so agents can build on them
  • Spreading our team’s best ways of working so everyone benefits
AI is also creating new ways for us to have impact. Some of us are growing our builder side. Some generalists are relying less on adjacent functions to deliver projects. Others are solving deep technical problems they’d never have had time to tackle before.Each new generation of models changes the answers, so we keep updating our priors.We’re looking for people who want to help shape how a modern analytics team works with AI.

Hear from our leaders

What I love about Analytics here is how close we are to the business’s most important decisions. Our teams work on complex problems across Deliveroo, DoorDash, and Wolt, and we expect people to understand the business deeply, know their numbers, develop a point of view, and make recommendations that move things forward.

We care about solving real problems and seeing the work translate into impact. Our teams define the right problem, get to the root of what is happening, bring clear recommendations, surface trade-offs, and follow through to understand what happened next. That takes curiosity, rigor, strong business judgment, and a willingness to challenge assumptions and bring new ideas. Our best work changes an action and helps the business move forward with greater clarity and confidence.

The scale and complexity of our businesses create an incredible environment to do that. You can work on problems that span consumers, merchants, riders, business verticals, and countries, with real ownership and influence over what decisions are made. If that kind of responsibility and impact motivates you, I think you’ll find this a really exciting place to build your career.

Jessica Lachs
Chief Analytics Officer

My own path into data science was unconventional. I came to the UK to pursue a PhD in Maths while training as a professional judo athlete, then moved into software engineering before finding my way into data science. That experience has shaped how I build teams: great Data Scientists and Analytics Engineers can come from many different backgrounds and paths.

What makes the work here particularly interesting is the complexity of the marketplace. A seemingly simple change can have effects across consumers, merchants, riders, our economics, and the broader system. That creates fascinating problems to solve. You need to frame the right question, understand how the system fits together, experiment rigorously, and turn what you learn into action.

I care a lot about impact and about being pragmatic in how we get there. If you enjoy solving hard problems, learning quickly, and seeing your work shape real products and decisions across markets, you’ll find a lot to get excited about here!

Mahana Mansfield
VP Data Science
Two employees laughing together whilst sat at a table
Two employees laughing together whilst sat at a table

Interested in joining us? We’re growing our EMEA Data Science team and would love to hear from you. Explore our current opportunities and find your place on the team.