Data Scientist (MMM)

Summary

Responsibilities

• Design and execute complex Marketing Mix Modeling frameworks to evaluate the effectiveness of various marketing channels.
  
• Analyze Adstock effects and calculate channel-specific contribution metrics, including Return on Marketing Investment (MROI).
  
• Develop and run incremental budget optimization scenarios to simulate potential outcomes and guide strategic financial planning.
  
• Create high-quality, interactive visualizations using libraries such as Matplotlib, Seaborn, and Plotly to communicate insights to stakeholders.
  
• Build, train, and validate robust statistical models, including regression, Bayesian, and hierarchical approaches, using Python, Pandas, NumPy, and Scikit-learn.
  
• Oversee the end-to-end lifecycle of machine learning models, ensuring seamless deployment, continuous monitoring, and maintenance through MLOps best practices.
  

• Minimum of 7 years of professional experience in data science, analytics, or a related quantitative field.
  
• Proven expertise in Marketing Mix Modeling (MMM) and a deep understanding of its application in modern marketing ecosystems.
  
• Strong proficiency in statistical modeling, specifically in regression analysis, Bayesian inference, and hierarchical modeling techniques.
  
• Advanced technical skills in Python, including extensive experience with data manipulation libraries (Pandas, NumPy) and machine learning frameworks (Scikit-learn).
  
• Demonstrated ability to implement Adstock transformations and calculate channel-level ROI and MROI.
  
• Competence in building and managing MLOps pipelines for model deployment and performance monitoring.
  
• Exceptional data visualization capabilities using Matplotlib, Seaborn, and Plotly to translate complex data into actionable business intelligence.