Data Analyst - Sortation & First Mile

Relay

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 network runs on forecasts. How many parcels arrive tomorrow. Which ones to sort tonight. How many shifts to release. When those forecasts are wrong, the cost shows up in CPP: too few shifts and you pay surge premiums, too many and you waste capacity. Behind each forecast is a model, and those models need someone watching them, catching drift, and surfacing problems before they hit operations. As Lead Data Analyst for the Network squad, you will own the analytical oversight across Relay's forecasting systems. That means tracking model performance across demand forecasting, shift planning, dimensions, and BPP inclusion. When a model starts missing, you catch it. When forecast error costs money, you quantify it. When stakeholders say "the forecast was wrong," you investigate and build the case for what to fix. This is not a model-building role. The Network squad's Data Scientists build and ship the forecasting models. Your job is to ensure those models keep working, to set analytical standards for the squad, and to be the first line of defence when something breaks. You will work closely with Sortation, Middle Mile, Last Mile, Routing, and Finance to understand where forecasts are working and where they're not. 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 Network squad, reporting to the Squad Lead. Depending on your experience, this role also offers line management opportunities. What You'll Do * Track forecast accuracy across all Network models: demand forecasts, shift planning forecasts, dimensions model, BPP inclusion models * Surface model drift and performance issues before they impact operations - you're the early warning system * Diagnose forecast errors by client, geography, day of week, and horizon, and quantify the CPP impact * Build dashboards that make model performance transparent to the squad and stakeholders * Set analytical direction for the Network squad: define what metrics matter, where to invest analytical effort * Work with Data Scientists to build the business case for model improvements, whether that's new input signals, data quality fixes, or client-specific treatment * Monitor how capacity matches demand across Sortation, Middle Mile, Last Mile, and track shift release effectiveness * Translate model performance into business impact that stakeholders can act on Who Will Thrive in This Role? * You catch problems before they become crises - you're vigilant about when models start behaving unexpectedly * You're obsessive about data quality and forecast accuracy - you hold models accountable for their predictions * You're fluent in SQL and experienced with dbt/BigQuery - you can build and maintain analytical models * You've built dashboards that are operationally critical, not just "nice to have" * You have a passion for forecasting and predictive modelling - you're energised by understanding where predictions hit and where they miss * You translate technical performance into business impact - CPP, surge costs, wasted capacity * You're comfortable challenging Data Scientists when models aren't performing, and working with them to improve * You communicate clearly with operations teams and can explain what the data shows without the jargon * You have at least 5 years of experience as a data analyst or similar role * You care about impact more than insight - you measure success by whether forecasts drive better decisions 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.

Relay

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 network is scaling fast. The decisions that shape that growth - where to expand, how to price, where to invest - rest on models that simulate how the network behaves and how it evolves as density, geography, and operating models change. We have an MVP tool for this today; we need someone to help productionise it and build the next generation of strategic models on top of it. You'll be a core contributor to Relay's digital twin - a network simulator that captures our unit economics end-to-end, from first-mile collection through sortation, middle-mile and last-mile. It's already in use by finance, but it's a living system: every operating-model change, new service type, or commercial scenario means upgrading a component, adding a model, or building a new view. Your job is to help keep it accurate and to extend it where the business asks new questions. Your remit splits roughly equally between two halves: 1. Evolving the digital twin. You understand each cost component deeply, you help identify where the current models are wrong or incomplete, and you upgrade them systematically. * When a new first-mile operating model is rolled out, you upgrade that engine. * When a new service type changes sortation cost, you understand it at a granular level and model it properly. * You add new flows, surface new metrics, and harden the parts that matter most for the decisions being made. 2. Building new strategic models and forecasts. Volume forecasts, predictive models, new scenario tooling - work that sits inside or alongside the twin. * You help decide what should live in the twin and what should stand alone. * You pick the right tool for the question - classical statistical modelling, financial modelling, simulation, or ML where it earns its place. Your primary partner is the finance team - Strategic Finance, Commercial Finance, FP&A. You translate their questions into modelling problems and give them tools that let them explore pricing, margin and projection scenarios dynamically rather than waiting for analysis to be rebuilt manually. You contribute to the roadmap - taking in their needs, helping prioritise what to build, and shipping it. You're part of a data org of around 30 engineers, analysts, and data scientists, but embedded in the finance squad. A dedicated finance analyst within the squad partners with you directly - they build the reporting and visibility layer on top of your models and feed prioritisation back to you. You'll work alongside more senior data scientists who own the broader direction of the twin. Who will thrive in this role * You're a strong modeller who thinks in systems. You naturally break complex problems into components, understand the assumptions behind each one, and know when those assumptions need revisiting. * You're a builder. You don't wait for requirements to be handed to you. You go and understand the problem, figure out what's needed, and ship something useful. Then you iterate. * You're fluent in Python and SQL, and comfortable doing your own data engineering. You can pull, transform, and model data without needing someone else to prepare it for you. * You bring strong software engineering principles into your modelling work. The digital twin is a real production system - Python, SQL, APIs, a frontend - and you'll work across that stack. You don't need to be a frontend specialist, but you should be at ease in a production codebase: writing tested, readable code, designing modular components, shipping changes that someone else can pick up next week. * You have experience with financial modelling, forecasting, or simulation, ideally in a context where your models informed commercial or strategic decisions - not just produced analysis. You know your way around ML and use it where it materially improves accuracy. * You communicate clearly with non-technical partners. Finance will rely on your models to make decisions. You need to explain what they do, where they're reliable, and where they're not. * You care about the problem more than the technique. You'll use whatever modelling approach fits. The point is accuracy, speed, and usefulness - not methodological elegance. * You take ownership of your work. You manage trade-offs and hold yourself accountable for whether the models are actually driving better decisions. * Logistics or delivery network experience is a plus, but what matters more is the ability to learn a complex operational domain quickly and model it well. Compensation and Benefits * 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). 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.

Relay

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 Overview Relay's Pitstop network is the convenience-store backbone of the operation. Customers drop off and collect parcels at these locations, Middle Mile drivers hand off and pick up, and the whole network depends on independent retailers behaving in ways that make Relay work. They aren't Relay staff. We don't control their attention, their turnover, or what else is happening behind their counter. Every behaviour we need has to be produced through systems, incentives, and the app. The Pitstop squad's job is to build those systems. Today the network runs at around 170k parcels a day, propped up by a small operations team and twelve LiveOps FTE absorbing the day-to-day breakage. The squad's mission is to take the network from 170k to 2M parcels a day without LiveOps scaling linearly with it. That means systematising launch readiness, pitstop performance, pricing structure, and retention so the same number of operators can support a network twelve times the size. As a Data Analyst in the Pitstop squad, you will own the analytics that make all of this measurable. Are launches hitting day-1 quality? Is handover speed improving where new in-app behaviour nudges have rolled out? Which pitstops are heading for churn and why? What's actually driving LiveOps ticket load, and which interventions are removing it? You'll build the monitoring layer the squad relies on, run the cost and performance investigations that shape what gets built next, and become the squad's source of truth on what's working. 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 Pitstop squad, working day-to-day with operations, sales, engineering, design, and research. You will report into the centralised data team and be line managed by the Lead Data Analyst for Middle Mile, Pitstops & Sortation. What You'll Do * Own the Pitstop squad's five outcome metrics: Launch Velocity, Handover Speed, Handover Accuracy, Pitstop Retention, and Indirect Cost per Parcel. Build the monitoring around them, investigate movement, and translate the numbers into next actions for the squad. * Run the analytics behind pitstop performance and pricing: which behaviours move handover speed, how commercial tiers and clawbacks are landing, which pitstops are systematically under- or over-performing, and what the in-app nudges are actually changing on the counter. * Quantify the impact of squad initiatives in cost terms: how much LiveOps load did this self-serve flow remove, how much Middle Mile driver time did this handover prompt unlock, and what is the CPP impact of retention work on mature pitstops. * Build launch readiness analytics: cohort ramp curves, time-to-maturity, where new pitstops break in week one, and how the launch playbook should evolve as volume grows. * Build the retention layer: a health score for pitstops, at-risk alerting, churn diagnosis triaged by cause, and the feedback loop back into acquisition and onboarding. * Investigate LiveOps ticket load by category and reason. Quantify what each ticket type costs, where the volume is concentrated, and which pillars should systematise it next. * Define KPIs and build dashboards that make Pitstop performance transparent to the squad, to operations, and to leadership. * Maintain and extend the squad's dbt models and data pipelines that underpin the monitoring layer. WHO WILL THRIVE IN THIS ROLE? * You want to understand how an operation actually works, not analyse it from a distance. Pitstops are messy, varied, and behaviour-driven. The best work comes from people who can sit with operators, watch handovers happen, and translate what they see into measurable signals. * You're excited by cost and behaviour problems. Where is LiveOps spending time, what's driving handover friction, and where are systems failing in ways the data can show but the squad cannot yet feel. * You can navigate messy operational data and turn it into metrics people trust. * You're comfortable working alongside operations, design, engineering, and commercial stakeholders, and you can embed your analysis into their 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 exposure to logistics, parcels, retail operations, or another network-scale operational business. * You care about impact, not just insight. Success in this role is measured by whether the Pitstop network can scale without LiveOps scaling with it. * You communicate clearly with non-technical stakeholders and can explain what the data shows, where the limits are, and what to do next. 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.