Data Analyst - Network

Data Analyst - Network 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. Every day, models predict how many parcels will arrive, which ones to sort tonight, how many shifts to release, and how many bags each route needs. When those predictions are right, operations run smoothly. When they drift, the cost shows up fast: routes cancelled from a dimensions model that shifted, surge premiums from under-predicted volumes, wasted capacity from over-forecasting. As a Data Analyst in the Network squad, you will monitor and interrogate the performance of every model the squad owns - demand forecasts, collection predictions, parcel dimensions, shift planning, and demand management allocation. The focus is analytical oversight rather than model building: Is accuracy holding? Where is bias creeping in? Which clients are the models struggling with? Why did Tuesday's forecast miss by 12%? When something is off, this role involves investigating the root cause, quantifying the impact, and collaborating with the Data Scientists to fix it. This requires strong dashboarding skills. You'll build the monitoring infrastructure that makes model performance visible to the squad and to the downstream teams that depend on these forecasts. You'll also develop a deep understanding of these models - their strengths, their weak spots, their failure modes - so the squad can catch changes early. 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 into the centralised data team. You'll work closely with Sortation, Middle Mile, Last Mile, and Routing - the squads that rely on the accuracy of the forecasts you're monitoring. What You’ll Do - Provide analytical oversight of the Network squad's models - demand forecasts, collection predictions, dimensions, shift release, and demand management allocation - in collaboration with Data Scientists and engineers - Investigate forecast errors by client, sort centre, day of week, and horizon - not just "accuracy is 92%" but "accuracy drops to 78% for TikTok on Mondays and here's what that costs us" - Quantify the CPP impact of model errors, working with the squad to understand how a 5% shift forecast miss translates into surge premiums or wasted capacity - Build dashboards that the squad and stakeholders rely on - accuracy tracking, bias monitoring, drift detection, model comparison before and after changes - Design alerting that surfaces model degradation before it hits operations, contributing to the squad's early warning capability - Partner with Data Scientists to validate model changes: did that retrain actually improve things, or did it just shift the error somewhere else? - Investigate when things go wrong - a forecast missed badly, a model drifted, a client's behaviour changed - working wit ... (truncated, view full listing at source)