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The Coca-Cola Company

Sells soft drink concentrates to bottlers worldwide

Data Scientist

Data ScienceConfirmed live in the last 24 hours
Full-timeShanghai, ChinaNo salary listed

About the Job

Requirements

  • 10–15+ years of experience in data science, advanced analytics, artificial intelligence, machine learning, or quantitative analytics within complex global organizations.
  • Proven experience developing and deploying predictive models, machine learning solutions, statistical analyses, and AI applications that deliver measurable business value.
  • Strong expertise in machine learning, predictive modeling, optimization, experimentation, and statistical analysis.
  • Experience programming in Python, R, SQL, and modern data science frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
  • Experience partnering with Data Engineering, Product Management, and Digital organizations to operationalize analytical solutions.
  • Demonstrated success translating complex analytical findings into strategic business recommendations for executive leadership.
  • Strong business acumen with experience supporting Commercial, Marketing, Supply Chain, Finance, or Customer functions.
  • Experience with cloud analytics platforms (Azure, AWS, or GCP), modern data platforms, and AI-enabled technologies.
  • Proven leadership experience developing high-performing technical teams and fostering innovation.
  • Fluent in English and Mandarin, with the ability to engage senior stakeholders across functions in a fast-paced environment.
  • Agile Methodology.
  • Business Process Modeling.
  • Change Management.
  • Cloud Platform.
  • Data Flow Diagram.
  • DevOps.
  • Digital Transformation.
  • Enterprise Architecture Framework.
  • Microsoft Azure Databricks.
  • Microsoft Office.
  • User Experience (UX).

Responsibilities

  • 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 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.
  • Drive enterprise business outcomes by transforming data into predictive insights and AI-powered decision capabilities.
  • Influence strategic decisions through advanced analytics, forecasting, optimization, and business intelligence.
  • Enable Operating Units and business functions to make faster, more informed decisions through scalable analytical solutions.
  • Partner across Commercial, Supply Chain, Finance, Marketing, and Digital organizations to solve high-value business challenges.
  • Establish enterprise standards and best practices for data science, model development, and analytical excellence.
  • Develop organizational capability in AI, machine learning, and data-driven decision making.
  • Solve highly complex business problems using advanced statistical methods, machine learning, optimization, and AI techniques.
  • Develop innovative analytical approaches for ambiguous business challenges with incomplete or evolving data.
  • Balance technical rigor with practical business application to maximize organizational value.
  • Leverage emerging AI technologies, generative AI, and advanced analytics platforms to improve business performance.
  • Continuously evaluate new algorithms, methodologies, and technologies to advance enterprise analytical capabilities.
  • Partner with senior business and digital leaders to define analytical priorities and translate business challenges into data science opportunities.
  • Present complex analytical findings in clear, actionable business language that drives executive decision-making.
  • Influence cross-functional stakeholders through data-driven recommendations and measurable business outcomes.
  • Collaborate closely with Product, Engineering, Data, and Business teams to deliver integrated analytical solutions.
  • Build 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.

About the Company

The Coca-Cola Company

Sells soft drink concentrates to bottlers worldwide

The Coca-Cola Company owns and markets beverage brands sold around the world, including Coca-Cola, Sprite, Fanta, Dasani, Powerade and fairlife. Its flagship cola has been sold in the United States since 1886 and anchors a portfolio spanning sparkling drinks, water, sports drinks, coffee, tea, juice and dairy. Rather than bottling most drinks itself, it sells concentrates and syrups to a franchised network of independent bottlers, which package and distribute finished beverages. It earns most revenue from those concentrate sales, plus finished drinks from bottlers it owns. The company was incorporated in 1892 and is headquartered in Atlanta, Georgia.

Company size
10,001+
Company stage
IPO
Headquarters
Atlanta, GA
Founded
1892

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