Marketing Data Scientist - MMM Specialist (Remote) 3-month project assignment. Base pay range: $73.00/hr - $83.00/hr. Location: Remote (Based in Dallas, TX). Weekly pay and benefits. This pay range is provided by TCWGlobal; your actual pay will be based on your skills and experience talk with your recruiter to learn more. Our client is seeking an experienced Marketing Data Scientist with deep expertise in Media Mix Modeling (MMM) to join their marketing analytics team. The ideal candidate will have 3+ years of professional Python experience, hands-on experience with Google Meridian or similar MMM frameworks, and strong capabilities in MMM validation, anomaly detection, and results synthesis. This role will be instrumental in optimizing marketing spend allocation and measuring campaign effectiveness across multiple channels. 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 Qualifications

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 Phyton 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 Preferred Qualifications

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) Seniority level

Associate Employment type

Full-time Job function

General Business and Science Industries

Technology, Information and Media

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