Senior Manager Data Scientist, Store Operations

JCPenney; Dallas (TX); On-site; USD 97,000 - 162,000; Full time

Benefits offered by this job

Medical/dental/vision insurance from @

401(k) with company match

Associate discount on JCPenney merch

Job summary

Catalyst Brands seeks a Sr Manager, Data Scientist for Store Performance & Operations to drive data‑driven improvements across 1,800 stores. You will apply advanced analytics, AI/ML modeling, and retail expertise to translate data into actionable insights for Store Ops, Field Leadership, Merchandising, and Finance.

The role shapes KPI dashboards, informs scheduling, allocation, and profitability, and requires 10+ years of analytics experience and leadership capabilities within a retail setting.

Qualifications

• Experience with forecasting, optimization, and segmentation using ML/AI tools.
• Strong analytical judgment in noisy data environments.
• Ability to interpret P&Ls and operational KPIs.
• Retail or operational exposure preferred.

Responsibilities

• Develops and applies analytics models diagnosing store performance drivers.
• Identifies underperforming stores and recommends interventions.
• Designs test‑and‑learn standards to evaluate initiatives and translate results.

Skills

Analytics leadership

Store operations knowledge

Data visualization

Communication

Problem solving

Cross-functional collaboration

Education

Master’s degree in Data Science or related field

Bachelor’s degree in Data Science, CS, Statistics, Mathematics, or related fields

Tools

Python

SQL

Job description

Overview

Sr Manager, Data Scientist – Store Performance & Operations

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.

Store Operational Performance & KPI Analytics

• 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).

Advanced Analytics for Store Optimization and Insights

• 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.

Influence, Leadership & Communication

• Present 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.

Qualifications

• 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

Store Operational Performance & Analytics

• Develops and applies analytics models that diagnose store performance drivers, including traffic, conversion, UPT, AUR, labor utilization, shrink, and improved margin profitability
• Identifies underperforming stores, quantifies root causes, and recommends targeted interventions (labor scheduling, product placement, assortment, training, process redesign).
• Designs and applies rigorous test‑and‑learn standards and approaches to evaluate operational and merchandising initiatives, translating results into clear recommendations and scalable actions.

Advanced Analytics for Store Optimization and Insights

• Creates models to detect operational patterns, identify key causal factors, and predict outcomes based on leading indicators.
• Develops predictive and decision‑support models for scheduling, staffing coverage, fulfillment flows, and allocation decisions that affect store performance and profitability.
• Transforms operational data—POS, labor, tasking, shrink events, foot traffic—into intelligence that supports rapid experimentation and decision‑making.
• Continuously refines models and reporting to adapt to evolving store strategies, customer behaviors, and brand needs.

Influence, Leadership & Communication

• Present 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.

Qualifications

• 6-10+ years of advanced analytics/data science experience, retail preferred or other operationally intensive environments with consumer exposure.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related fields; Master’s degree is a plus.
• Demonstrated success delivering analytics solutions, including forecasting, optimization, and segmentation, using ML models and AI tools that drive measurable operational or financial outcomes.
• Strong analytical judgment in noisy data environments, with the ability to identify and validate relevant data, distinguish causal from predictive questions, make valid comparisons, surface bias and assumptions, and translate model outputs into sound business conclusions.
• Financial and operational acumen, able to interpret P&Ls and operational KPIs.
• Influential written and verbal communication skills, able to guide decision‑making without direct authority.
• Ability to model and promote a culture of intellectual honesty, constructive skepticism, shared ownership, continuous improvement, and practical rigor to drive improved business decisions.
• Proficient in Python and SQL, able to build and validate reproducible workflows, including AI‑assisted code.

What You Get:

Enjoy a rewarding career at Catalyst, where we offer a competitive benefits package, a vibrant work environment, and the opportunity to make a difference at one of America's most iconic brands.

• Generous Benefits: Medical/dental/vision insurance starting on day one, term life insurance, paid vacation/holidays, 401(k) Savings Plan with company match, and an associate discount on JCPenney merchandise.
• Opportunities for Growth and Development: We are committed to helping our employees grow their careers and develop their skills. We offer a variety of training and development programs, as well as opportunities for advancement.
• Collaborative and supportive Culture: We believe in creating a workplace where everyone feels valued and respected. We encourage teamwork and collaboration, and we are always looking for ways to support our employees' success.

About Catalyst:

Catalyst Brands reflects the bringing together the rich heritages of our brands with modern excitement and a new vision for success. Six iconic brands came together under a unified powerhouse portfolio to celebrate the essence of American style. We will leverage our rich history, resources and best‑in‑class industry talent to further build the success of our brands. At Catalyst we are united in one shared purpose: We exist to ignite America’s most beloved retail brands to make fashion accessible to all.

For more opportunities to join our team please visit our careers page.

Pay Range

USD $97,200.00 - USD $162,000.00 /Yr.