Marketing Data Scientist - MMM Specialist

About the Role

Key Responsibilities

• Develop and maintain sophisticated Media Mix Models using Google Meridian, Lightweight MMM, or similar frameworks, implementing advanced techniques including Bayesian statistical modeling, adstock transformation, saturation curves, and diminishing returns modeling
• Design and execute MMM experiments and validation frameworks to measure incrementality, media effectiveness, and ensure model reliability through holdout tests, geo-experiments, sensitivity analysis, and automated performance monitoring
• Build production-ready MMM systems using Python and modern data engineering practices, creating scalable, code-based solutions that integrate with existing marketing technology stacks and data warehouses
• Implement comprehensive quality assurance processes including anomaly detection systems, robustness testing, and automated alerts to maintain data quality and model performance over time
• Conduct scenario planning and budget optimization using MMM insights to drive strategic marketing investment decisions and resource allocation
• Translate complex analytical findings into actionable business recommendations through compelling visualizations, executive dashboards, and strategic presentations to marketing teams and senior leadership
• Synthesize results across multiple models and validation approaches to provide robust, data-driven recommendations for marketing strategy and budget allocation
• Optimize model performance for computational efficiency and scalability while implementing version control and reproducible modeling workflows for enterprise-level deployment

Requirements

• 3+ years of professional Python experience with strong proficiency in data science libraries (NumPy, Pandas, SciPy, Scikit-learn) and SQL
• 2+ years of marketing analytics experience with strong understanding of digital marketing channels, campaign structures, media buying processes, and marketing data sources (ad platforms, CRM, sales data)
• Must be able to pass Python assessment
• Hands-on experience with Google Meridian MMM (Media Mix Modeling) or other leading MMM frameworks (Lightweight MMM, Meta Robyn, PyMC-Marketing) including backend code-based MMM system development
• Strong statistical and modeling expertise in Bayesian statistics, time series analysis, econometric modeling, and probabilistic programming frameworks (JAX, Numpyro, PyMC, Stan)
• Deep MMM validation and quality assurance skills including holdout testing, incrementality measurement, model calibration, and anomaly detection for marketing data
• Advanced analytical capabilities including results synthesis across multiple validation approaches, marketing attribution, causal inference methods, and experimental design (A/B testing, geo experiments)
• Excellent communication and collaboration skills with ability to present complex statistical concepts to non-technical stakeholders and work cross-functionally with marketing, data engineering, and business intelligence teams

Nice to Have

• Direct Google Meridian implementation experience and customization capabilities
• Bachelors, Master's or PhD degree in Statistics, Data Science, Economics, Marketing Analytics, or related quantitative field with strong foundation in statistical modeling and experimental design
• Experience with cloud platforms (GCP preferred, AWS, Azure) for large-scale MMM deployment and real-time optimization systems
• Background in econometrics, marketing science, or advertising research with publications or presentations on MMM methodologies
• Knowledge of marketing experimentation platforms, incrementality testing tools, and data visualization platforms (Tableau, Looker, Plotly)

Qualifications

• 3+ years of professional Python experience
• Strong proficiency in data science libraries and SQL
• Experience with MMM frameworks and validation techniques