Senior Data Scientist – Store Performance & Operations
Indexed description
This role partners closely with Store Operations, Merchandising, and Finance to translate business problems into analytical approaches, deliver actionable insights, and help establish sound measurement and testing practices for operational changes and model-driven recommendations.
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.
- 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.
Influence, Leadership & Communication
- 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.
- 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.
- 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.
For more opportunities to join our team please visit our careers page.
Pay Range
USD $97,200.00 - USD $162,000.00 /Yr.
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