Director, Data Science

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.

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