Location: Atlanta, GA (Global HQ)
Estimated Travel: 0-20%
Direct Reports: None
The Global Equipment Platforms (GEP) team is seeking an exceptional and highly skilled Data Scientist to unlock the profound value hidden within the telemetry data of The Coca-Cola Company’s global fleet of 17MM+ connected equipment. Reporting to the Head of Data within GEP Digital, this individual contributor role is crucial in transforming raw data from beverage vending machines, dispensers, coolers, and retail racks into actionable intelligence that drives revenue growth, reduces operating expenses, and provides unprecedented real-time market understanding.
You will be at the forefront of designing, developing, and deploying advanced analytical models, machine learning algorithms, and potentially AI Agents, leveraging vast datasets from equipment running on the KO Operating System (KOS) and other embedded systems. This role demands a deep technical expert with a proven track record of extracting insights from complex, high-volume data, building robust predictive solutions, and effectively communicating findings to influence strategic decisions across our internal teams, 200+ global franchise bottlers, and OEM partners. Your work will directly enable predictive maintenance, optimize equipment placement, personalize consumer experiences, and inform real-time commercial strategies.

REQUIRED EXPERIENCE & QUALIFICATIONS:

• Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or a related discipline. Master’s or Ph.D. preferred.
• 7+ years of hands-on experience as a Data Scientist, with a strong portfolio of successfully deployed machine learning models in production.
• Expertise in statistical modeling, machine learning algorithms (supervised, unsupervised, reinforcement learning), and deep learning.
• Highly proficient in programming languages commonly used for data science (Python required, R a plus) and relevant libraries (scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
• Strong experience with cloud-based ML platforms and services, particularly Microsoft Azure Machine Learning, Azure Databricks, and related data services.
• Demonstrated ability to work with large, complex, and often messy datasets, including time-series data from IoT devices.
• Proficiency in SQL for data extraction and manipulation.
• Experience in data visualization tools (e.g., Power BI, Tableau, matplotlib, seaborn).
• Strong understanding of MLOps principles and practices for model deployment and lifecycle management.
• Experience with, or strong understanding of, IoT, connected devices, and telemetry data.

SKILLS:

Scikit-Learn; Data Science; Python (Programming Language); Statistical Models; Microsoft Azure Databricks; Data Visualization; Tensorflow; PyTorch; Machine Learning Operations; Pandas Python Library; Microsoft Azure Machine Learning; Machine Learning Algorithms; Deep Learning
All persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form (Form I-9) upon hire.
Pay Range:$131,000 - $153,000
Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:15
Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target