Data Analyst, Operations Strategy

Michaels-posted 11 days ago
Full-time • Mid Level
Irving, TX
5,001-10,000 employees
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The Data Analyst, Operations Strategy will apply advanced analytics, predictive modeling, and data mining to help drive retail and omni-channel performance. This role will uncover actionable insights into customer behavior, store performance, and operational efficiency, supporting strategic initiatives such as store of the future, labor optimization, portfolio planning, and omni-channel integration. A successful candidate will be able to comfortably translate large amounts of raw data into digestible insights for operations leadership. Additionally, this individual will be able to anticipate the data needs of leadership in order to assist in successfully storytelling and/or control narratives.

  • Develop and deploy predictive models to forecast customer demand, labor productivity, and omni-channel adoption (Buy Online Pick-up In Store, Curbside, Ship From Store).
  • Conduct data mining across retail, customer, and financial datasets to identify patterns, opportunities, and risks.
  • Support competitive intelligence analysis by modeling external market and competitor data.
  • Partner with Reporting Analyst to integrate models into dashboards and KPIs.
  • Provide ad hoc analytics for senior leadership, including scenario planning and sensitivity analyses.
  • Ensure data governance, accuracy, and consistency in all Operations datasets.
  • Translate technical findings into clear, actionable business recommendations for executives.
  • Other duties as assigned
  • 3–5+ years of experience in applied analytics, preferably in retail, e-commerce, or consumer industries.
  • Proficiency with SQL, Python, R, or other modeling languages.
  • Expert in Microsoft Suite products, especially Excel.
  • Hands-on experience with predictive modeling, clustering, regression, and machine learning techniques.
  • Familiarity with retail data sources (POS, customer transactions, omni-channel fulfillment, real estate/store data).
  • Expert in Power BI (data modeling, DAX, measures, visuals).
  • Proven ability to turn analytics into compelling executive-ready presentations.
  • Strong problem-solving and hypothesis-driven approach.
  • Ability to communicate complex analytics to non-technical audiences.
  • Collaborative, with ability to partner across operations, finance, and merchandising.
  • Intellectually curious.
  • Willing/unafraid to ask questions.
  • Expert in pulling data quickly and effectively.
  • Anticipates leadership’s daily, weekly, and quarterly data needs through solid understanding of the business and operations.
  • Bachelor’s or Master’s degree in Data Science, Statistics, Applied Mathematics, Computer Science, or related field.
  • health insurance (medical, dental, and vision)
  • paid time off
  • tuition assistance
  • generous employee discounts
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