Senior Manager Data Scientist, Store Operations @Catalyst Brands
Data and Analytics
Salary usd 97,200 - 16..
Remote Location
🇺🇸 USA Only
Employment Type full-time
Posted 1mth ago

[Hiring] Senior Manager Data Scientist, Store Operations @Catalyst Brands

1mth ago - Catalyst Brands is hiring a remote Senior Manager Data Scientist, Store Operations. 💸 Salary: usd 97,200 - 162,000 per year 📍Location: USA

Role Description

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.

Benefits

  • 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.

Company Description

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.

Before You Apply
🇺🇸 Be aware of the location restriction for this remote position: USA Only
Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more.
Senior Manager Data Scientist, Store Operations @Catalyst Brands
Data and Analytics
Salary usd 97,200 - 16..
Remote Location
🇺🇸 USA Only
Employment Type full-time
Posted 1mth ago
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🇺🇸 Be aware of the location restriction for this remote position: USA Only
Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more.
Apply for this position
Did not apply
Applied
Sent Follow-Up
Interview Scheduled
Interview Completed
Offer Accepted
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Application Denied
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