• Lead national‑level advanced analytics initiatives (e.g., revenue & demand forecasting, demand sensing, promo effectiveness/ROI, and scenario planning) that inform pricing, channel strategy, and investment decisions. • Build and operationalize statistical/ML models (time series, causal inference, uplift modeling) that scale across geographies, customer segments, and product lines. • Deliver complex, executive‑ready ad hoc analyses (often with imperfect or incomplete inputs) for commercial leaders with fast, with clear, defensible recommendations. • Develop repeatable analytics assets (code, feature stores, data marts) and documentation so work is durable, auditable, and easy to extend. • Own stakeholder engagement: intake, prioritization, transparency on trade‑offs; shape hypotheses; align on success metrics; and tell the story in a way leaders can act. • Raise the bar on data quality and governance: define critical data elements, implement controls/monitoring, and partner with Data Stewardship to improve reliability of business‑critical datasets. • Build high‑confidence executive dashboards (Tableau) and automated pipelines that reduce manual reporting and shrink time‑to‑insight.