Senior Data Scientist - Network Simulation

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, figur