Senior Data Scientist - Relay Network

Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M), Relay is scaling faster than 99.98% of venture-backed startups. Relay’s Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone.

THE TEAM

• ~110 people, more than half in engineering, product and data
• 45+ advanced degrees across computer science, mathematics and operations research
• Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle
• An intellectually vibrant culture of first‑principles thinking, tight feedback loops and relentless experimentation

About the role

Relay's network runs on forecasts. Every shift released in sortation, every middle-mile van dispatched, every last-mile route planned, every expansion decision made - all downstream of models that predict how parcels move through our system. When those models are right, the network runs efficiently and cost per parcel drops. When they drift, the cost compounds across every stage of the operation. The Network squad builds and maintains the forecasting engine that powers all of it. As a Senior Data Scientist in the Network squad, you will lead a core domain within that engine, working alongside other Data Scientists and Analysts who each bring different expertise. The scope spans demand forecasting, expansion modelling, parcel intelligence, and sortation predictions - and the specific domain you take on will depend on your strengths and what the squad needs most.

What You'll Do

• Build and maintain forecasting models within your domain - from initial exploration through to validation and production deployment
• Learn the operational processes your models serve, supported by the squad and the teams who use the forecasts, and identify where the current approach falls short
• Monitor how your models perform in production, investigate when accuracy drops, and work with the squad to improve them
• Contribute to methodology decisions and validation approaches, working with other Data Scientists in the squad to improve the forecasting engine over time
• Translate problems from consuming squads into data science problems - Sortation, Middle Mile, Last Mile, Routing, and Commercial each depend on Network's forecasts
• Work with Finance, who extend the operational forecasts into longer-range financial projections, to ensure the handoff between operational and financial models is reliable
• Quantify the impact of model errors on cost per parcel, helping the squad and stakeholders prioritise where to invest effort
• Influence the squad's technical direction and modelling approaches as the team grows

Who Will Thrive in This Role?

• Experience thinking about interconnected systems - understanding that a demand forecast isn’t just a number, but flows through shift release, van dispatch, route planning, and courier allocation.
• A track record of building and delivering models.
• Strong Python and SQL, and comfort working across the modelling lifecycle - from data extraction and feature engineering through to model training, validation, and production deployment.
• You’ve worked with time-series forecasting methods - whether classical statistical approaches, gradient boosting, deep learning, or a combination - and you understand the trade-offs between them.
• You have at least 5 years of experience in a data science or quantitative modelling role, with examples of models you built that informed operational or commercial decisions.
• You’ve taken models from notebook to production - writing maintainable code, building pipelines that run reliably, and debugging when they don’t.
• You have experience communicating with non-technical stakeholders.
• You’re comfortable using AI tools - LLMs, code assistants, and similar - to accelerate your workflow.
• This role suits someone who wants to see whether their models made a real difference to how the network operates.

Compensation, Benefits & Workplace

• Generous equity, richer than 99% of European startups, with annual top-ups to share Relay’s success.
• Private health & dental coverage.
• 25 days of holidays.
• Enhanced parental leave.
• Located in Shoreditch, our office set-up enables the kind of in-person interactions that drive impact.
• We work 4 days on-site, with 1 day remote.
• Hardware of your choice.
• Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more).

Who Thrives at Relay?

• Aim with Precision: You define problems clearly and measure your impact meticulously.
• Play to Win: You chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction.
• 1% Better Every Day: You believe that small, consistent improvements lead to exponential growth.
• All In, All the Time: You show up and step up.
• People-Powered Greatness: You invest in your teammates.
• Grow the Whole Pie: You seek out win‑win solutions for merchants, couriers, and our customers.

Relay is an equal-opportunity employer committed to diversity, inclusion, and fostering a workplace where everyone thrives.