Analyst, Supply Chain Planning

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The Analyst, Supply Chain Planning is responsible for providing the analytical foundation on which our demand, supply, and inventory decisions are made, and for driving the improvement initiatives that advance our planning capability over time. This role sits within the Planning team alongside our demand and supply planners: where they own the execution of the forecast and the replenishment plan, you own the analysis, diagnostics, and reporting that make those decisions sharper, faster, and more defensible. You will build and automate the recurring performance reporting the team runs on, investigate and explain variance rather than simply surface it, and translate large, complex datasets into recommendations leadership can act on. This position offers broad exposure across forecasting, replenishment, and inventory strategy, and a direct path to grow into a planning or analytics leadership role as our team’s scope expands.

One of the first tactical initiatives for this role will be building out our store sales performance and replenishment analytics. As our retail showroom footprint grows alongside e-commerce, we need clear visibility into how each location sells, where availability is constraining sales, and how inventory should be allocated and replenished across the network.

You will own the analysis that establishes that visibility and turns it into a repeatable replenishment approach. We are a hands-on, code-forward planning organization. Our forecasting, replenishment, and reporting run on a Python-native analytics stack rather than on manual spreadsheets, and every member of the team is expected to work fluently in SQL, Python, and BI tooling. This is how we operate, and it is central to how this role creates value.

Responsibilities:

• Analytics, Reporting & Performance Management
• Build, automate, and maintain the recurring reporting and dashboards the Planning team operates on, including forecast accuracy and bias, service level and fill rate, inventory turns, weeks of supply, replenishment health, and fulfilment mix Extract, clean, and reconcile data across multiple source systems into trustworthy, decision-ready views, applying disciplined validation before any number is published
• Define and track planning KPIs against target, developing exception reporting that surfaces risk early rather than after the fact
• Investigate variance to root cause and explain the drivers behind it, distinguishing genuine demand signal from data quality, seasonality, and one-off effects