# Director, Supply Chain Lead Data Scientist at Coca-Cola

Coca-Cola is hiring a Director, Supply Chain Lead Data Scientist in Atlanta, United States. It pays $164k-$193k a year and Level rates it Builds AI ●●●●; you can [apply on Coca-Cola](https://jobsbylevel.com/go/a1365112-725d-4db6-b2cd-dc2d13f6da89?utm_medium=ai-agent).

AI Level 4, AI centrality 88 out of 100. US - GA - Atlanta.

## Details

- Company: [Coca-Cola](https://jobsbylevel.com/companies/coca-cola)
- AI level: AI Level 4 (score 88 out of 100)
- Location: US - GA - Atlanta
- Salary: $164k-$193k
- Posted: November 10, 2026
- Apply: https://jobsbylevel.com/go/a1365112-725d-4db6-b2cd-dc2d13f6da89?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=director-supply-chain-lead-data-scientist-at-coca-cola-b1c6cc

## Prepare for this job

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## Description

Job Description Summary: Job Summary Supply Chain Digital Enablement applies data, analytics, and artificial intelligence to improve planning, service, cost, resilience, and execution across the North America Operating Unit. Our teams turn complex operational decisions into scalable digital capabilities that create measurable value for customers, bottlers, and the business. Our work spans demand planning, inventory and replenishment, transportation, manufacturing, customer service, and network decisions. Strong data foundations, rigorous experimentation, optimization, and responsible AI are essential to building solutions that teams trust and use. About the Role As a Data Scientist in Supply Chain Digital Enablement, you will build analytical products that improve how supply-chain teams make decisions. You will partner with Supply Chain, Operations, Product, Engineering, Data, Commercial, and Finance colleagues to translate ambiguous business problems into scalable models, optimization tools, simulations, and AI-enabled decision support. This role combines statistical analysis, predictive modeling, optimization, simulation, and modern AI techniques. You will lead the technical direction for complex, high-value solutions and establish reusable architecture, MLOps, evaluation, and governance practices that raise capability across the team. We are looking for someone with intellectual curiosity, technical rigor, practical supply-chain judgment, and a collaborative approach to delivery. What You Will Do Develop, evaluate, and productionize predictive, prescriptive, optimization, simulation, and NLP models for supply-chain decisions Translate planning, inventory, transportation, manufacturing, network, and service problems into clear analytical requirements, model approaches, and measurable outcomes Design ML architectures and rapid prototypes; partner with Engineering and Data teams to scale successful solutions into reliable products Apply optimization and simulation methods, evaluating algorithmic complexity, performance, scalability, and trade-offs Apply statistical analysis, forecasting, causal methods, and experimental design to evaluate interventions and quantify business impact Partner with data engineering to ensure trustworthy data architecture, scalable pipelines, robust querying, instrumentation, and data-quality foundations Build model lifecycle practices including reproducibility, versioning, testing, deployment, monitoring, drift detection, retraining, and documentation Evaluate and apply deep learning, large language models, NLP, and agentic systems where they create measurable value with appropriate controls and human oversight Apply AI governance, privacy, security, fairness, explainability, and responsible-AI principles throughout development and deployment Communicate technical choices, assumptions, insights, limitations, and recommendations clearly to technical and nontechnical stakeholders Contribute to cross-functional software lifecycle management from discovery and prototyping through deployment, adoption, support, and continuous improvement Define technical strategy, reference architectures, and modeling standards for priority supply-chain data-science products Mentor data scientists and review technical designs, model quality, deployment readiness, and responsible-AI controls What You Will Need Key Qualifications 7+ years applying data science, machine learning, optimization, forecasting, or advanced analytics in a business, digital, operations, or supply-chain environment Demonstrated technical leadership delivering complex data-science products from problem definition through production adoption and measurable business impact Advanced Python and SQL skills and experience designing scalable data, model, and ML architecture patterns Deep expertise in several of predictive modeling, optimization, simulation, statistical inference, experimental design, NLP, deep learning, or agentic systems Experience

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