Senior Manager Data Scientist, Store Operations

Catalyst Brands

$97K — $162K *
Retail & Consumer Goods
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related fields
  • 10+ years of advanced analytics/data science experience in retail or operationally intensive environments
  • Proven ability to deliver analytics and AI solutions that yield measurable operational outcomes
  • Strong understanding of store operations and financial levers
  • Expertise in financial and operational metrics including P&Ls and labor impacts
  • Strong critical thinking and problem-solving skills
  • Influential communication with the ability to guide without direct authority

Responsibilities

  • Develop and apply analytics models to diagnose store performance drivers
  • Design KPI frameworks and dashboards for visibility into performance
  • Identify underperforming stores and recommend targeted interventions
  • Create models to detect operational patterns and predict sales outcomes
  • Build AI-driven tools for optimizing scheduling and profitability
  • Transform operational data into actionable insights
  • Define data governance standards for accurate store-level reporting

Benefits

  • Opportunities for professional development and continuous improvement
  • Collaboration with cross-functional teams to enhance store performance
  • Impact on enterprise-wide decision-making
  • Possibility of influencing strategy in a fast-paced retail environment
Full Job Description
Overview

The Senior Data Scientist delivers practical analytical solutions to improve store performance, labor effectiveness, and operations decision-making across the 5 brands and 1,400 stores at Catalyst Brands. The role uses strong and disciplined analytical judgement in concert with advanced analytics and modeling, building causal and predictive models that drive sound business decisions. The Senior Data Scientist uses AI-enabled analytical and development tools to improve speed, quality, and breadth of analysis.

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.

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
• 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.

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.

Pay Range

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

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