Data Scientist, Data & Analytics - Customer, Loyalty & Marketing

Circle K Stores-posted 2 months ago
Charlotte, NC
5,001-10,000 employees
Food and Beverage Retailers
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As part of the Global Data & Analytics Team, we are seeking a skilled and business-savvy Data Scientist focusing on Marketing Analytics and Marketing Mix Modeling (MMM). This role will play a critical part in helping us understand and optimize the impact of our marketing investments across various channels (TV, digital, social, search, retail, etc.). The candidate will work closely with Marketing, Finance, and Data teams to deliver data-driven insights that drive strategic and tactical decision-making. He should have hands-on experience building MMMs, interpreting results for business stakeholders, and integrating those insights into actionable marketing recommendations.

  • Develop and maintain Marketing Mix Models to measure effectiveness of TV, radio, digital, out-of-home, print, and in-store promotions.
  • Translate complex statistical outputs into clear, actionable insights for Marketing, Finance, and Leadership teams.
  • Build in-house models using Python/R/other languages. Conduct scenario simulations and budget allocation optimization.
  • Monitor data pipelines and ensure data quality and granularity (sales, media spend, promotions, weather, seasonality, store traffic).
  • Contribute to broader analytics strategy, including incrementality testing, geo-experiments, and attribution modeling.
  • Facilitate best practice sharing and contribute to automation and improvement of existing processes.
  • Present actionable insights and recommendations to marketing business managers to influence business strategies and continuously enhance the value generation from loyalty programs.
  • Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Data Science, Economics, Applied Mathematics, Computer Science).
  • 3+ years' experience in MMM, econometrics, or media effectiveness analysis. Strong background in statistics/econometrics (e.g., linear regression, time series, Bayesian models).
  • Proficient in data wrangling and visualization using tools like Pandas, SQL, Power BI, or Tableau.
  • Proficiency in query processing languages such as SQL and PySpark, along with hands-on experience on cloud-based platforms (e.g., Azure).
  • Excellent communication skills with the ability to clearly articulate technical information to all levels of the organization and collaborate effectively with cross-functional teams.
  • Strong stakeholder management skills, with experience engaging diverse teams and senior leaders across geographies.
  • Collaborative and proactive, with the initiative to drive projects to successful completion.
  • Adaptable to new and evolving technologies and business needs. Curious and committed to continuous learning in both business and technology domain.
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