Senior Manager Data Scientist, Store Operations

JCPenney•Dallas, TX

About The Position

The Sr Manager, Data Scientist – Store Performance plays a mission-critical role in advancing Catalyst Brands’ ability to use data to optimize store operations, accelerate sales, and improve profitability. This leader applies advanced analytics, AI/ML modeling, and deep retail expertise to uncover the operational and customer-experience drivers that fuel business outcomes across 1,800 stores. This role serves as the analytical thought partner to Store Operations, Field Leadership, Merchandising, and Finance—translating complex data into actionable insights that enhance productivity, improve KPI performance, and guide strategic investments. The position influences enterprise-wide decision-making and elevates Catalyst’s data-driven operating culture.

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.

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 detects 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.