Senior Product Analyst, Unit Economics

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. Most delivery companies sell on price and volume, and find out later whether a client made them money. Sales teams are measured on what they sign, not on what a signing is worth. Relay wants every client, and every new shop in the network, to be one we'd choose again. That is harder for us than for most, because what a client is worth depends on how their parcels flow through a network that's still growing. Engineering and analytics engineering build what you design. Sales Highlights You own decision-making, not the model: you decide what a client or shop is worth and which signings sales should chase. The sales lead acts on your calls. What is a new client or a new shop worth, when its value depends on where it sits in a network that changes every month? What would you build so sales knows before it signs? Which signings become partners who do well with us, and what does that tell sales to look for? The quarter's target is set. What has to close by when for it to hold, and what would tell you early that it won't? A whole area, not a slice: you decide how sales values what it wins, and the result shows in what we sign next. 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 Senior Product Analyst, Unit Economics at Relay, you'll: Decide which Sales problems are real and which only look real, before anyone builds a fix. Design how Sales decides: which signals count, what a client or shop is worth, and what good looks like. Tell the sales 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 numbers and the street disagree: a new shop, a client's parcels at the sort centre. Get the missing data built, and prove whether each change worked. In a year, sales chooses what to go after on measures you built, and can see whether the quarter will land before it ends. We're looking for candidates who… Have owned B2B pricing or commercial decisions and their number, rather than maintaining sales dashboards. Have built, hands on, the first version of how a company values a customer or a deal: unit economics, lifetime value, or what it costs to win one. Have seen their work acted on: a leader changed a plan, a team adopted your method, or sales went after different deals because of it. Have got records created by teams who didn't report to you, and know how long it takes. Can say early whether a quarter