Data Scientist, Data & Analytics Customer, Loyalty & Marketing

About the Role

Key Responsibilities

• 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, or 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 enhance loyalty programs.

Requirements

• 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).
• Proficiency in data wrangling and visualization using tools like Pandas, SQL, Power BI, or Tableau.
• Proficiency in query processing languages such as SQL and PySpark.
• Hands-on experience on cloud-based platforms (e.g., Azure).
• Excellent communication skills to articulate technical information and collaborate effectively.
• Strong stakeholder management skills and experience engaging diverse teams and senior leaders.
• Collaborative, proactive, and adaptable to new technologies and business needs.
• Curious and committed to continuous learning in business and technology domains.

Nice to Have

• Experience with scenario simulations and budget optimization.
• Experience with attribution modeling and incrementality testing.
• Knowledge of marketing channels such as TV, digital, social, search, retail.

Qualifications

• Bachelor's or Master's degree in a relevant quantitative field.