Senior Data Scientist - Operational Research

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 A last-mile marketplace runs on decisions - which parcels? on which routes? delivered by which couriers? at what price? Thousands of them, made every single day. Good decisions have fast and meaningful impact across the entire Relay Network. We’re hiring for a Senior Data Scientist to build the intelligence that informs and defines how we make pricing decisions at Relay. This is a senior individual contributor role. You will work alongside Operational Research Scientists, Analysts, and Engineers in a collaborative squad focussed on developing the intelligence, strategy and technology to deliver 1000’s of daily pricing decisions. What You'll Do You won’t just inform the pricing decisions, you will be an equal part of the team defining how the decision is being made and building the technology to automate it. In this role you can expect: * Through your own investigation, to become an expert in Relay marketplace pricing dynamics, using it to define how routes are priced. * To build and maintain production models that inform the daily pricing decisions. * To experiment and measure the impact of model improvements or pricing strategy changes. Who Will Thrive in This Role * You're a strong modeller who thinks in systems. * You care about solving the problem above all else * You love working with smart, motivated people * You’re fluent in python and SQL * You communicate inclusively with non-technical team members * You are successful working with high autonomy * You love seeing the impact of your work play out in a daily operation * You have experience modelling marketplace dynamics, pricing strategies or another relevant domain. 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. * 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. 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 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's common across all of it: you will build and maintain models that directly drive operational decisions for multiple teams across Relay, every day. This means different things depending on the domain. It might mean building the expansion models that determine where Relay grows next: which outcodes to enter, how volumes ramp in new areas, and how the pitstop network should evolve. It might mean working on the dimensions model that predicts parcel weights and sizes before they arrive, feeding route planning and vehicle loading decisions. It might mean extending the demand forecast horizon from 7 days toward 30, giving downstream teams more lead time to plan. Or it might mean improving the predictions that determine what volume is available to sort on a given night, and how that volume should be allocated across sort centres. Relay operates a centralised data team of around 30 Data Engineers, Analysts, and Data Scientists, with specialists embedded into squads across the business. You will sit in the Network squad alongside other Data Scientists and Analysts, reporting into the centralised data team. The squad is growing, and you will have significant influence over its technical direction and the modelling approaches it adopts. You will be supported by Analysts who build the monitoring and reporting layer, and a squad lead who sets strategic direction. 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. You're interested in how your models connect to the models around them. * A track record of building and delivering models. You've worked from ambiguous starting points before - understanding the problem, building something useful, validating it against real operations, and iterating. You evaluate models beyond standard offline metrics - connecting outputs to downstream applications and business KPIs, and measuring how improvements translate into operational impact. The squad works collaboratively to define priorities and scope, and you'll have support from the squad lead and your peers as you ramp up * 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. Experience with data engineering is useful, and you'll be supported by a dedicated engineer in the squad. * 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've contributed to methodology decisions and understand that a model isn't done when it trains well; it's done when it's running, monitored, and trusted. * You have experience communicating with non-technical stakeholders. The squads that consume the forecasts need to trust them, and that trust comes from explaining what the models do, where they're reliable, and where they're not. * You’re comfortable using AI tools - LLMs, code assistants, and similar - to accelerate your workflow, from exploratory analysis to code generation, and you're curious about where these tools can augment the modelling process itself. * This role suits someone who wants to see whether their models made a real difference to how the network operates - there is a direct feedback loop between your work and operational outcomes. * 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, 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. * 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. 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.