Director, Predictive Modeling

Job Description 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.

What You'll Do

• 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.

Required Qualifications

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.

Experience

• 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.

Technical Expertise

• 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.

Communication & Collaboration

• 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.

Preferred Qualifications

• 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.

What We'll Do for You

• 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.

The Coca-Cola Company will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment-based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full-time basis and must not require The Coca-Cola Company's sponsorship to continue to work legally in the United States.

Skills: Causal Inference, Cloud Analytics, Collaboration, Cross-Functional Collaboration, Data Engineering, Data Storytelling, Data Visualization, Data Wrangling, Econometrics, Feature Engineering, Forecasting, Git Version Control System, Machine Learning (ML), Market Mix Modeling (MMM), Model Validation, Optimization Models, Predictive Modeling, Problem Solving, Python (Programming Language), R Programming, Statistical Models, Structured Query Language (SQL), Time Series Analysis

Pay Range: United States of America: 169,000 USD - 200,000 USD

Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.

Annual Incentive Reference Value Percentage: 30

Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.

Location(s): United States of America

City/Cities: Atlanta

Travel Required: 00% - 25%

Relocation Provided: No

Job Posting End Date: August 13, 2026

Our Purpose and Growth Culture:

We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.