Digital Product Analytics Owner analyzing digital user behavior to optimize experiences and provide insights. Collaborating cross - functionally to enhance product strategies and drive decision - making.
About the role
- Senior Manager, Data Scientist optimizing store operations with advanced analytics and AI models. Collaborating with leadership to drive data-driven decisions and improve store performance.
Responsibilities
- Develops and applies analytics models that diagnose store performance drivers, including traffic, conversion, UPT, AUR, labor utilization, shrink, and improved margin profitability.
- Designs KPI frameworks and dashboards that give field and corporate leaders visibility into store performance and improvement opportunities.
- Identifies underperforming stores, quantifies root causes, and recommends targeted interventions (labor scheduling, product placement, assortment, training, process redesign).
- Creates models to detect operational patterns, segments store behaviors, and predicts sales outcomes based on leading indicators.
- Builds AI driven tools that optimize scheduling, staffing coverage, fulfillment flows, and allocation decisions that impact store profitability.
- Transforms operational data—POS, labor, tasking, shrink events, foot traffic into intelligence that supports rapid experimentation and decision-making.
- Defines and improves data governance standards to ensure the accuracy, granularity, and timeliness of store-level reporting and analytics.
- Continuously refines models and reporting to adapt to evolving store strategies, customer behaviors, and brand needs.
- Presents insights and performance diagnostics to store leadership, distilling complex analytics into clear narratives that guide operational strategy.
- Partners with Store Operations, Finance, Merchandising, and Field Leadership to align analytics outputs with business priorities.
- Guides cross-functional initiatives that drive measurable improvements in sales, labor productivity, customer satisfaction, and overall store profitability.
Requirements
- Master’s degree or equivalent experience in Data Science, Computer Science, Statistics, Mathematics, or related fields.
- 10+ years of advanced analytics/data science experience, ideally within retail or operationally intensive environments.
- Demonstrated success delivering analytics solutions using analytics and AI solutions that drive measurable operational or financial outcomes.
- Strong business insight and strategic mindset, with a deep understanding of store operations and financial levers.
- Financial and operational acumen, able to interpret P&Ls, labor metrics, margin impacts, and operational KPIs.
- Critical thinking and problem-solving, capable of diagnosing complex store challenges using data.
- Influential communication, able to guide decision-making without direct authority.
- Team leadership, building high-performing, analytics-forward teams.
- Continuous improvement orientation, driving innovation in tools, processes, and insight delivery.
- Expert-level data collection, cleansing, and analysis.
- Retail KPI modeling, forecasting, optimization, and simulation.
- Data architecture and workflow optimization for store analytics.
- Insights reporting, visualization, and operational storytelling.
- Business requirements development and action planning for performance improvement.
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