Data Scientist

Job Description Summary:
The Coca‑Cola Company is evolving into a more digital‑first, data‑driven enterprise to fuel sustainable growth, increase speed to market, and unlock new sources of value. Rapid advances in technology, data, and AI create a unique opportunity to accelerate the KO system’s next chapter of growth by reimagining our core competitive advantages. Building on a strong foundation of modernized infrastructure, global digital experiences, early data capabilities, and proven use cases, we are now shifting from early wins to scaled, end to end impact on growth, productivity, and efficiency.
This next phase moves us from an analog world to a fully digitized one, powered by a digital growth engine that embeds data, technology, and AI into our most critical business domains. Success will require more than technology implementation, it demands a strategic transformation of core capabilities, a domain based, product centric operating model, and a cultural shift toward experimentation, data and technology fluency, and seamless partnership between business and digital teams.
Job Description Summary
The Director, Data Science is responsible for leading advanced analytics, machine learning, and AI initiatives that transform enterprise data into actionable business insights and strategic decision-making. This role partners closely with business leaders, Product teams, Digital Services, and Operating Units to identify high-value opportunities, develop predictive models, and deliver scalable analytics solutions that drive growth, productivity, and operational excellence.
The Director combines deep expertise in data science, statistical modeling, and AI with strong business acumen to solve complex business challenges and enable data-driven decision making across the Coca-Cola system. Working across multiple functions, the role translates business problems into analytical solutions, builds intelligent products and models, and ensures insights are embedded into business processes to maximize value realization.
Success in this role requires strong technical leadership, analytical thinking, strategic problem-solving, and the ability to communicate complex insights in ways that influence business decisions.
Responsibilities include:
Lead the development and execution of advanced analytics, machine learning, and AI solutions that address strategic business priorities.
Partner with business stakeholders to identify opportunities where data science can improve growth, productivity, customer experience, and operational performance.
Design, develop, and deploy predictive models, machine learning algorithms, optimization models, and statistical analyses to solve complex business problems.
Transform large, complex datasets into actionable insights, recommendations, and decision-support capabilities.
Develop scalable analytical products, reusable models, and AI-enabled solutions that drive measurable business value.
Partner with Product, Data Engineering, and Digital teams to operationalize machine learning models and integrate analytics into digital products and business workflows.
Evaluate model performance, monitor business outcomes, and continuously refine analytical approaches to improve accuracy and effectiveness.
Establish best practices for data science, experimentation, model governance, feature engineering, and responsible AI.
Communicate analytical findings through compelling business storytelling, executive presentations, and visualization tools that influence strategic decisions.
Mentor and develop data scientists while fostering a culture of innovation, experimentation, and continuous learning.
Stay current on emerging AI, machine learning, and advanced analytics technologies, identifying opportunities to accelerate business transformation.
ORGANIZATIONAL IMPACT
Drives enterprise business outcomes by transforming data into predictive insights and AI-powered decision capabilities.
Influences strategic decisions through advanced analytics, forecasting, optimization, and business intelligence.
Enables Operating Units and business functions to make faster, more informed decisions through scalable analytical solutions.
Partners across Commercial, Supply Chain, Finance, Marketing, and Digital organizations to solve high-value business challenges.
Establishes enterprise standards and best practices for data science, model development, and analytical excellence.
Develops organizational capability in AI, machine learning, and data-driven decision making.
INNOVATION & COMPLEXITY
Solves highly complex business problems using advanced statistical methods, machine learning, optimization, and AI techniques.
Develops innovative analytical approaches for ambiguous business challenges with incomplete or evolving data.
Balances technical rigor with practical business application to maximize organizational value.
Leverages emerging AI technologies, generative AI, and advanced analytics platforms to improve business performance.
Continuously evaluates new algorithms, methodologies, and technologies to advance enterprise analytical capabilities.
COMMUNICATION & INFLUENCE
Partners with senior business and digital leaders to define analytical priorities and translate business challenges into data science opportunities.
Presents complex analytical findings in clear, actionable business language that drives executive decision-making.
Influences cross-functional stakeholders through data-driven recommendations and measurable business outcomes.
Collaborates closely with Product, Engineering, Data, and Business teams to deliver integrated analytical solutions.
Builds trusted relationships across the organization to promote data literacy and a culture of evidence-based decision making.
Perform other job‑related duties as assigned, in response to evolving business needs and market dynamics.
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