Data Scientist

About The Coca-Cola Company and Digital Transformation

The Coca-Cola Company is advancing toward becoming a digital-first, data-centric enterprise to support sustainable growth, accelerate speed to market, and unlock new value sources. Embracing modern infrastructure, enhanced digital experiences, early data practices, and proven use cases, the company is transitioning from initial successes to delivering wide-scale impact on growth, productivity, and operational efficiency. This shift requires a strategic transformation involving a product-focused operating model, cultural change encouraging experimentation, fluency in data and technology, and close collaboration between business and digital teams.

Role Overview

The Data Scientist (Manager, Data Science) in the ASEAN & South Pacific Operating Unit will lead the development and implementation of advanced analytics, machine learning, and Agentic AI solutions designed to enhance business outcomes. This role demands both strong technical expertise and the capability to partner with business leaders to address challenges spanning commercial, marketing, finance, and strategic domains. The individual will oversee the full lifecycle of AI-powered analytics products, ensuring successful adoption and value realization.

Key Responsibilities

• Develop predictive models for revenue growth, market share expansion, demand forecasting, customer acquisition, and commercial performance.
• Design prescriptive analytics frameworks to recommend optimal business actions and resource deployment.
• Apply sophisticated statistical, machine learning, and optimization methods to solve complex challenges.
• Communicate analytical findings into actionable business strategies.
• Construct, validate, and deploy machine learning models across diverse domains including commercial, marketing, finance, strategy, and franchise.
• Build scalable AI applications using structured and unstructured data sets.
• Enhance model performance, accuracy, explainability, and relevance continually.
• Collaborate with external partners to support AI solution production deployment.
• Design and deploy Agentic AI solutions automating analysis, insight generation, and decision support.
• Create AI agents capable of reasoning across multiple data sources and analytics outputs.
• Implement Retrieval-Augmented Generation, orchestration frameworks, and decision-support agents.
• Identify high-impact use cases for autonomous or semi-autonomous AI agents to improve productivity and decision-making quality.
• Contribute to the development of AI-driven business processes and self-service analytics capabilities.
• Translate business requirements into scalable analytics products and reusable models.
• Work with product managers, data engineers, and SMEs in agile teams to deliver solutions that achieve measurable outcomes and user adoption.
• Build strong partnerships with stakeholders in strategy, franchise, finance, marketing, commercial, and digital functions.
• Facilitate business case development and value quantification for analytics projects.
• Articulate complex analytic concepts clearly to business audiences.
• Train and empower business users in leveraging AI-based decision-making tools.

Required Qualifications

• Master's or Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or a related discipline.
• 8 to 10 years of professional experience in data science, machine learning, advanced analytics, or related fields.
• Proven track record of delivering AI and analytics solutions from conceptualization to full production deployment.
• Experience collaborating with business stakeholders to address commercial or operational challenges with data-driven methods.

Technical Expertise

• Traditional AI and machine learning techniques such as supervised/unsupervised learning, time series forecasting, classification and regression models (preferably including Bayesian approaches), ensemble models like Random Forest, XGBoost, and LightGBM, deep learning, and optimization tools (Pyomo, PuLP, SciPy).
• Model explainability techniques such as SHAP and LIME.
• Agentic AI and generative AI technologies including large language models (LLMs), agentic AI frameworks, retrieval-augmented generation architectures, prompt engineering, AI orchestration, multi-agent systems, copilot, and enterprise AI platforms.
• Programming in Python and SQL.
• Familiarity with Azure AI Services, Databricks, Microsoft Fabric, Power BI, Git, MLFlow, and MLOps tooling.

Benefits and Work Environment

• Opportunity to join a forward-looking, award-winning technology team operating at the forefront of innovation.
• Access to global technology leaders, expanding professional networks and exposure to emerging technologies.
• Agile work culture promoting experimentation, iteration, and innovation with supportive management removing barriers.

Additional Information

Location: Singapore
Travel Requirements: 0% to 25% travel involved
Relocation Assistance: Not provided
Annual Incentive: Market-competitive with 15% reference value indicating performance at target

The company's culture highlights inclusion, curiosity, empowerment, and agility supporting continuous learning and improvement aligned with its purpose to refresh the world and make a difference.