Data Analyst - Sortation & First Mile

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 (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% 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
• ~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

The Opportunity

Relay’s Hybrid Sort Centres are where parcels enter the network, get sorted into routes, and flow out to delivery. Sortation is operationally complex: warehouse operatives, intake scanners, supervisors, and robots all working together to process thousands of parcels daily. First Mile is how those parcels arrive - collections from retailers, with all the variability that brings. Together, these domains sit at the start of the network and set the pace for everything downstream.

As a Data Analyst in the Sortation & First Mile squad, you will own the analytics for both domains. The work is broad: cost investigations, workforce planning, capacity analysis, performance tracking, and operational reporting. Your analysis won’t sit in a dashboard waiting to be discovered - it will shape how shifts are scheduled, how volumes are managed, and where the operation focuses its improvement efforts.

Relay operates a centralised data team of around 30 data engineers, analysts, and data scientists, with analysts embedded into squads across the business. You will sit in the Sortation & First Mile squad, but report into the centralised data team. You’ll work closely with operations, commercial, and finance to turn data into decisions that affect how the network runs every day.

What You’ll Do

• Investigate cost per parcel: where are we spending too much, where are savings available, and what’s driving the variance

• Track operative performance across roles: throughput, accuracy, shift utilisation, and the balance between direct and agency labour

• Monitor robot efficiency and capacity: what volumes can they sustain, where are the bottlenecks, how do they compare to manual processing

• Build models to predict shift requirements and automate workforce planning, prioritising top-performing operatives

• Analyse injection volumes and manifest accuracy: how much are we actually sorting vs. what’s forecast, and where are the gaps

• Define KPIs and build dashboards that make sortation and first mile performance transparent to operations and leadership

• Work with commercial teams to set volume limits and injection timing that balance growth with operational stability

Who Will Thrive in This Role?

• You want to understand how an operation actually works, not just analyse it from a distance

• You’re excited by cost problems - finding where money is leaking and building the case for how to fix it

• You can navigate messy operational data and turn it into metrics people trust

• You’re comfortable working with operations teams and embedding your analysis into their daily workflows

• You’re fluent in SQL and experienced with BI tools, with strong problem-solving instincts

• You have at least 3 years experience, ideally with some exposure to logistics

• You care about impact, not just insight - you measure success by whether the operation runs better

• You communicate clearly with non-technical stakeholders and can explain what the data shows and where the limitations are

Fast and Focused Hiring Process

1. Talent Acquisition Interview - 30mins | Online

2. Hiring Manager Interview - 45mins

3. SQL Live Coding - 60mins

4. Case Study - 60mins

5. Relay Operating Principles & Impact- 60mins

6. Decision and offer within 48 hours. Our process mirrors our pace of work.

Compensation, Benefits & Workplace

• Generous equity, richer than 99% of European startups , with annual top-ups to share Relay’s success.

• Private health & dental coverage , so comprehensive you’d need to be a partner at a Magic Circle law firm to match it.

• 25 days of holidays

• Enhanced parental leave .

• Hardware of your choice .

• Extensive perks (gym subsidies, cycle-to-work, Friday office lunch, covered Uber home and dinner for late nights, and more).

• 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 .

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.