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Data Scientist
The Coca-Cola Company · Shanghai, China
Publicada em 10/09/2026
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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 SummaryThe 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 valu
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