Senior Data Analyst

Key Responsibilities

● Demand forecasting- Build and maintain forecasts at SKU and colour level. Test multiple model families and configurations, report accuracy across all of them, and recommend one on the evidence rather than on preference.

● Lifecycle and range analytics- SKU-level performance, concentration, and decline detection — the evidence base for deciding what is extended, what is replaced and what is retired.

● Replenishment segmentation- Segment the catalogue by volume and volatility and derive the policy parameters that follow for each group.

● New launch forecasting- Build analogue-based forecasts for products with no sales history, using comparable lines adjusted for price, season and placement.

● Data Integrity-Own validation of the numbers that reach a planning decision - reconciliation, freshness and anomaly checks - and raise a discrepancy before it reaches that decision rather than after.

● Returns analysis -Root-cause the drivers of returns and own the measured before-and after on every change made in response.

Required Experience

● 4 to 7 years in analytics within e-commerce, retail or supply chain, having owned models end to end rather than reported on someone else's.

● Strong SQL and Python for modelling and analysis.

● Real demand forecasting experience with an accuracy record you can state-what error you achieved, which models you tested, and why the one you chose to beat the alternatives.

● Comfortable working across a catalogue of several thousand active lines spanning colours and sizes.