Manager, Data Engineer

About Our Digital Transformation

The Coca-Cola Company is undergoing a shift to become a digital-first, data-centric enterprise aiming to enhance sustainable growth, accelerate speed to market, and generate new value sources. Leveraging advances in technology, data, and AI, the company focuses on moving beyond early successes to achieve end-to-end scale impact on productivity, efficiency, and growth. This transformation encompasses adopting a data, technology, and AI-infused approach within core business areas, necessitating strategy, cultural change, and stronger collaboration between business and digital teams.

Role Overview

As a Manager, Data Engineer, you will lead the design and delivery of advanced analytics, machine learning models, and Agentic AI solutions that impact business outcomes across the ASEAN & South Pacific region. Your role demands not only strong expertise in predictive and prescriptive analytics but also a partnership approach with business leaders to address commercial, marketing, financial, and strategic challenges end-to-end—from problem identification to solution deployment and value realization. You will be a pivotal driver supporting the organization's data-driven, AI-powered business evolution.

Key Responsibilities

• Develop predictive models to boost revenue, market share, demand forecasting, customer growth, and commercial success.
• Create prescriptive analytics that advise optimal business decisions and resource allocation.
• Utilize sophisticated statistical, machine learning, and optimization methodologies for complex business problems.
• Convert analytic insights into actionable recommendations for leadership teams.
• Build, validate, and roll out machine learning solutions in commercial, marketing, finance, and strategic domains.
• Develop scalable AI models using both structured and unstructured data sources while enhancing model accuracy and relevance.
• Assist in the production deployment of AI tools collaborating with external partners.
• Design and implement Agentic AI systems that facilitate automated analytics, insight generation, and decision support.
• Construct AI agents capable of multi-source reasoning and implement frameworks like Retrieval-Augmented Generation and orchestration.
• Collaborate with stakeholders to identify high-impact cases for autonomous or semi-autonomous AI to improve productivity and decision quality.
• Contribute to evolving AI-empowered business workflows and self-serve analytic capabilities.
• Transform business needs into scalable analytic products and reusable AI accelerators working within agile teams including product managers and data engineers.
• Ensure delivered solutions yield measurable business benefits and promote user uptake.
• Partner across functions such as Strategy, Franchise, Finance, Marketing, Commercial, and Digital to support business case creation and value analysis.
• Communicate complex analytics in straightforward business terms and train users on AI-driven decision tools.

Required Qualifications and Experience

• A Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or similar fields.
• 5 to 8 years practical experience in Data Science, Advanced Analytics, Machine Learning, or relevant areas.
• Proven track record delivering AI and analytics projects from conception to full deployment.
• Experience collaborating with business stakeholders to resolve commercial or operational challenges through data-driven methods.

Technical Competencies

• Expertise in supervised and unsupervised learning, time series forecasting, classification and regression models including Bayesian approaches.
• Familiarity with ensemble techniques such as Random Forest, XGBoost, LightGBM, plus deep learning algorithms.
• Optimization modeling using tools like Pyomo, PuLP, or scipy.
• Capability to explain models with methods such as SHAP and LIME.
• Knowledge of Agentic and Generative AI technologies including Large Language Models, RAG architectures, agentic AI frameworks, prompt engineering, and AI orchestration.
• Experience working with multi-agent systems and enterprise AI platforms including Copilot solutions.
• Proficiency with Python, SQL, Azure AI services, Databricks, Microsoft Fabric, Power BI, Git, MLFlow, and MLOps toolsets.

Additional Information

• Location: Singapore
• Travel: Approximately 0-25%
• Relocation: Not provided
• Culture: The company promotes an inclusive, growth-oriented culture focusing on curiosity, empowerment, inclusiveness, and agility to nurture continuous learning and innovation.
• Annual Incentive: Market-competitive with a reference value around 15% of salary.