Staff Decision Scientist, Marketplace

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. We're assembling the most talent-dense team the logistics industry has ever seen

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
• ~160 people, around 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

Relay delivers 400,000 parcels a day through people who don't work for us: van drivers who choose their own shifts, local shops that hold parcels, and couriers who take them to the door. We went from 3,000 parcels a day in London to 400,000 across the UK in under three years.

Delivery companies have always bought capacity by guesswork. Book too few drivers and parcels wait; book too many and you pay for empty vans. Most carriers accept that waste as the price of being reliable. Relay is building a marketplace where it isn't. You can't schedule drivers. You can only design what's on offer, and measure what happens.

Every part of our network runs on decisions. The next two years are about building the systems that make them well, and proving they do. Engineering and operational research build what you design.

Marketplace Highlights

• You own decision-making, not the model: you decide what Marketplace changes on booking, matching and shifts, and recommend on pay. Our scientists' models and experiments feed your calls, and the squad lead acts on them.

• Drivers choose when to work. What makes a shift worth booking early, and how do you prove what works when a clean experiment isn't possible?

• Every booked shift is paid, used or not, and every unserved route means late parcels. Where should each area sit between the two, and what would let the network get there on its own?

• Local shops hold our parcels while running their own businesses. Where does the network need more of them, what should a shop be paid, and how would you see a closed shop coming?

• A whole area, not a slice: no playbook, and the result is on the street the next morning.

• Analytics at the front, not in support: the squad's roadmap follows the analysis, in a data team of about 30 across analytics, operational research and data science.

The Opportunity

As a Staff Decision Scientist, Marketplace at Relay, you'll:

• Decide which Marketplace problems are real and which only look real, before anyone builds a fix.

• Design how Marketplace decides: which signals count, and what good looks like for booking, matching and pay.

• Tell the squad lead what to change and what to stop, and get a decision.

• Build the thing that decides: data applications, monitors and alerts, not decks, using Claude and agents to ship your own tools.

• Go and look when the data and the street disagree: the sort centre, the van, the shop.

• Get the missing data built, and prove whether each change worked. In a year, Marketplace's booking and pay decisions run on a system you designed.

We're looking for candidates who…

• Have owned the decisions a matching, pricing or incentive model fed, in a two-sided marketplace or gig platform, rather than building the model itself.

• Have seen their work acted on: a leader changed a plan, a team adopted your method, or engineers built what you asked for.

• Can trace why drivers or couriers stop booking or cancel, and can read the experiments behind a pricing or incentive change, including when a clean test isn't possible.

• Have been through real change, such as a pivot, fast growth or a new market, and rebuilt something because of it.

• Are hands-on and fluent in SQL, with or without AI, and happy to build their own analysis apps, monitors and alerts.

• Would rather ship a working answer this week than a perfect one next quarter. No logistics experience needed, just the appetite to learn a physical operation fast.

Don't tick every box? If this problem excites you, we'd still love to hear from you.

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. You move quickly, deliver results, and learn from every experience.

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

• People-Powered Greatness: You invest in your teammates. You give and receive feedback with care and candour. You build trust through high standards and shared success.

• Grow the Whole Pie: You seek out win-win solutions for merchants, couriers, and our customers, because when they thrive, so do we.
  
  If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let’s connect.

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