Role Summary

The Associate Manager leads delivery for a defined region/full reporting line, ensuring Business-As-Usual (BAU) stability while meeting client commitments. The role owns quality, on-time delivery, productivity, and continuous improvement outcomes by orchestrating people, process, and technology. This leader builds a high-performance culture, and collaborates with Transformation, Technology, and People (HR) to drive client satisfaction (NPS), automation of manual processes, and a great place to work.

Key Responsibilities

• Delivery & BAU Governance: Own day-to-day production for the region/reporting line; maintain BAU stability and recover quickly from incidents.
• Quality Management: Drive Right-First-Time outcomes through control plans, root-cause analysis, and preventive actions.
• On-Time Delivery (OTD): Plan capacity, balance workload, and remove blockers to achieve committed cycle times and SLAs.
• Cost & Efficiency: Improve unit cost and throughput via standard work, cross utilization and automation; prioritize transformation opportunities.
• Stakeholder Collaboration: Partner with Transformation & Tech to digitize manual processes; with People/HR to strengthen engagement, DE&I, and manager effectiveness.
• People Leadership: Coach and develop DOA and PDOA; build succession pipelines; foster psychological safety and high performance.
• Risk & Compliance: Identify and mitigate operational risks; ensure adherence to policies, data security, audit, and regulatory requirements.
• Performance Management: Define operating rhythms (stand-ups, WBR/MBR/QBR); publish dashboards and action plans for gaps
• Client Readiness & Change: Lead production readiness for new/changed work; plan migrations and transitions without service disruption.

KPIs & Outcomes

• Quality: First-Time-Right %, QE%
• On-Time Delivery: SLA adherence %, Cycle Time vs. plan, On-time release %.
• BAU Stability: Backlog age, Schedule adherence
• Productivity & Cost: Throughput per FTE, Automation coverage %, RPH trend, Utilization.
• Client Experience: Client escalations closed on time

People & Culture: Gallup score, Attrition %, Internal mobility

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.