Director, Predictive Modeling

Summary: At The Coca-Cola Company, data powers better decisions, stronger results, and smarter growth. The Modeling and Measurement team enables this by delivering predictive analytics that guide strategic priorities across our business.   As the Director of Predictive Modeling, you will serve as a senior technical expert responsible for designing, building, and deploying advanced statistical and machine learning solutions that answer high-impact business questions. This is a highly hands-on individual contributor role for an experienced data scientist who has spent years developing predictive models and analytics solutions from the ground up.   You will   leverage   advanced analytics, machine learning, econometrics, forecasting, and experimentation techniques to help leaders   optimize   investments, forecast outcomes, understand key business drivers, evaluate customer behavior, and assess strategic scenarios. Success in this role requires the ability to translate ambiguous business challenges into structured analytical problems and deliver scalable, defensible, and actionable solutions.   This role is intended for a deeply technical individual contributor who has a proven history of personally designing, coding,   validating , and deploying predictive modeling solutions. The ideal candidate enjoys working directly with data, building analytical frameworks from first principles, and developing production-ready solutions that influence business decisions.   In this role, you will collaborate with analysts, data engineers, product owners, marketers, and business stakeholders to develop modeling solutions that integrate into planning processes and decision-making workflows. Your work will ensure the accuracy, transparency, maintainability, and business relevance of predictive tools while helping foster a culture of evidence-based decision making across the organization.

Design, develop,   validate , and deploy predictive models using statistical, econometric, machine learning, and AI techniques.   Develop end-to-end analytical solutions, from data acquisition and preparation through model development, validation, deployment, and ongoing monitoring.   Write production-quality code to build scalable and maintainable analytical systems.   Perform extensive data wrangling, feature engineering, exploratory analysis, and data quality assessment across complex and imperfect datasets.   Develop forecasting, classification, regression, optimization, and causal inference solutions to address strategic business challenges.   Create decision-support tools, simulation frameworks, and scenario planning solutions that translate analytical insights into actionable business outcomes.   Partner with Marketing, IMX, Commercial, Data Engineering, and other cross-functional stakeholders to scope problems and align analytical solutions with strategic priorities.   Apply rigorous model validation techniques and communicate assumptions, limitations, and recommendations to both technical and non-technical audiences.   Develop analytical assets that are scalable, explainable, and designed for adoption within business workflows.   Establish modeling best practices related to reproducibility, documentation, validation, governance, and performance monitoring.   Evaluate emerging tools, platforms, and methodologies to continuously improve the organization's modeling capabilities.   Mentor peers and contribute to analytics community best practices and technical capability building across the enterprise.

Education   Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, Data Science, Operations Research, or a related quantitative field.   Master's degree preferred   or PhD in Statistics, Data Science, Economics, Mathematics, Computer Science, Operations Research, or a related quantitative discipline.

8-10+ years of