Director, Predictive Modeling

Coca-Cola • Atlanta, GA

1d • Onsite

About The Position

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.

Requirements

• Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, Data Science, Operations Research, or a related quantitative field.
• 8-10+ years of hands-on experience developing predictive modeling and machine learning solutions in industry, consulting, or applied research environments.
• Demonstrated experience independently building end-to-end analytical solutions, including data acquisition, cleaning, feature engineering, model development, validation, deployment, and business adoption.
• Proven ability to translate business problems into analytical frameworks and convert modeling outputs into measurable business impact.
• Experience partnering directly with senior business stakeholders and cross-functional teams.
• Advanced proficiency in Python (preferred) or R, with the ability to write efficient, maintainable, well-documented code.
• Extensive experience with data wrangling, data cleaning, feature engineering, exploratory data analysis, and data quality assessment.
• Strong SQL and database skills with experience working with large-scale datasets.
• Deep understanding of statistical inference, econometrics, machine learning algorithms, forecasting methods, model validation, and experimental design.
• Experience building analytical solutions using modern machine learning libraries and frameworks such as scikit-learn, LightGBM , XGBoost , PyTorch , TensorFlow, PyMC , Spark ML, or equivalent technologies.
• Experience with cloud analytics and machine learning platforms such as Databricks, Microsoft Fabric, Azure Machine Learning, AWS, Google Cloud Platform, Snowflake, Spark, or equivalent technologies.
• Experience with software engineering practices including Git, code reviews, testing frameworks, CI/CD, and reproducible analytical workflows.
• Proven ability to communicate complex analytical concepts to business stakeholders, technical teams, and executive audiences.
• Skilled at influencing decisions through data-driven storytelling, visualizations, and recommendation frameworks.
• Strong collaborator with experience working across technical and non-technical teams.

Nice To Haves

• Master's degree preferred or PhD in Statistics, Data Science, Economics, Mathematics, Computer Science, Operations Research, or a related quantitative discipline.
• Experience developing forecasting, pricing, measurement, optimization, marketing science, consumer analytics, or causal inference solutions.
• Experience in consumer packaged goods (CPG), beverage, retail, consulting, or adjacent industries.
• Experience deploying and supporting analytics solutions in production environments.
• Familiarity with MLOps , model monitoring, feature stores, and production analytics ecosystems.

Responsibilities

• 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.

Benefits

• Provide opportunities to lead advanced modeling initiatives that influence strategic decisions and major business investments.
• Offer access to cutting-edge analytics tools, cloud technologies, and large-scale global datasets.
• Enable collaboration with business leaders, engineers, and analytics professionals across The Coca-Cola Company.
• Support continuous learning, technical innovation, and thought leadership in advanced analytics and data science.
• Provide an environment where technical expertise , intellectual curiosity, and business impact are valued equally.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior