Lead Data Analyst - Network

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.

Responsibilities

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

Requirements

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