Job Summary
The Associate Manager – Statistical Operations leads end‑to‑end statistical and analytical operations supporting RMS and OMNI business planning and decision‑making. The role ensures high‑quality forecasting, universe‑level trend tracking, KPI validation, and Store & Sample Maintenance, along with overall operational rigor using internal, syndicated, and panel data.
This role partners closely with Analytics, Data Science, Sourcing, Transformation & Enablement, Business, Technology, and People (HR) teams to deliver reliable statistical outcomes while fostering strong team collaboration and associate development.
Statistical Operations
- Own end‑to‑end statistical operations across forecasting and analytics workflows, including data intake, validation, model inputs, output reviews, and downstream hand‑offs.
- Ensure accurate, timely, and SLA‑compliant delivery of forecasts, validated KPIs, universe metrics, and analytical outputs across RMS and OMNI processes.
- Monitor and assess universe‑level trends to ensure stability, consistency, and alignment across time periods and data sources.
- Perform KPI validation and data health checks, ensuring completeness, reasonability, and adherence to defined statistical standards.
- Lead Store & Sample Maintenance processes, including store and sample additions, removals, corrections, alignment, and ongoing universe maintenance.
- Ensure store‑ and sample‑level data integrity through regular validation, reconciliation, and impact assessments on forecasts and KPIs.
- Leverage panel and syndicated data to support forecasting, universe trend analysis, KPI validation, and statistical measurements.
- Support analytical enablement for new initiatives, pilots, and ongoing programs requiring statistical support or model updates.
- Manage historical and ongoing updates such as universe restatements, store/sample maintenance updates, trend adjustments, and KPI corrections, with strong governance and documentation.
- Review and validate statistical methodologies, assumptions, and outputs to ensure consistency across datasets, models, stores/samples, and time horizons.
- Conduct forecast and KPI performance reviews and drive continuous stability and accuracy improvement initiatives.
- Lead and contribute to cross‑functional analytical projects aimed at strengthening statistical processes and operational efficiency.
- Drive automation and process optimization initiatives to reduce manual effort, improve scalability, and enhance data reliability.
- Partner with Analytics, Data Science, and Transformation & Enablement teams to transition pilots into BAU operations.
Tools & Systems
- Hands‑on experience with R, Python, SQL, and Advanced Excel.
- Familiarity with enterprise forecasting, planning, or analytics platforms and data warehouse environments.
- Exposure to automation, scripting, or workflow optimization initiatives is preferred.