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.