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Senior Manager, Machine Learning Advanced Analytics

Atlanta, GA, US • Posted 19 days ago • Updated 2 hours ago

Full Time

On-site

The Coca-Cola Company

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Job Details

Skills

Advanced Analytics
OFA
Decision-making
Analytics
Workflow
Training
Evaluation
Data Science
Data Integration
Data Engineering
Performance Management
Mentorship
Cloud Computing
Microsoft
Amazon SageMaker
Google Cloud
Google Cloud Platform
Vertex
Artificial Intelligence
Python
Scripting
Version Control
Git
Continuous Integration
Continuous Delivery
GitHub
DevOps
Docker
Microsoft Azure
Kubernetes
ACS
Machine Learning (ML)
Software Engineering
Problem Solving
Conflict Resolution
Adaptability
FOCUS
Presentations
Collaboration
Effective Communication
Innovation
Network
Agile
Management

Advanced Analytics
OFA
Decision-making
Analytics
Workflow
Training
Evaluation
Data Science
Data Integration
Data Engineering
Performance Management
Mentorship
Cloud Computing
Microsoft
Amazon SageMaker
Google Cloud
Google Cloud Platform
Vertex
Artificial Intelligence
Python
Scripting
Version Control
Git
Continuous Integration
Continuous Delivery
GitHub
DevOps
Docker
Microsoft Azure
Kubernetes
ACS
Machine Learning (ML)
Software Engineering
Problem Solving
Conflict Resolution
Adaptability
FOCUS
Presentations
Collaboration
Effective Communication
Innovation
Network
Agile
Management

Summary

The Coca-Cola Company's Technology organization isin the midst ofa digital transformation that allows our employees to useworld classtechnology to connect our products to our customers all over the world. This journey is a very exciting time forCoca-Colaand our employees are big contributors to our Success and Growth. Our large scale and complex environmentoffersan incredible opportunity to address challenges, enable innovative solutions to make a difference for our customers.

In this position, you will embark on a journey ofleveragingvast amounts of data to transform it into actionable insights. You will aid in the development of analytics models and work under the guidance of seasoned data science professionals to drive decision-making and strategyacross the organization. This is an exciting opportunity togrow inyour career in data science and analytics within a supportive and innovative environment.

WhatYou'llDo for Us:

Model Deployment & Operationalization: Partner with data science teams to transition machine learning models from experimentation to production environments, packaging models into robust Docker containers for scalable and reproducible deployments.

Pipeline Automation: Build andmaintainautomated CI/CD pipelines for machine learning workflows (e.g., model training, evaluation, and deployment)utilizingtools like GitHub Actions. Leverage Azure Container Registry to securely manage container images and deploy scalable workloads to Azure Kubernetes Service (AKS) or Azure Container Instances (ACS).

Utilize Azure Machine Learning and Microsoft Fabric Data Science to manage the ML lifecycle. Adapt prior experience from other cloud platforms to effectively navigate andoptimizeour current stack.

Monitoring & Maintenance: Implement monitoring solutions to track model performance, data drift, and system health in production. Ensure comprehensive logging and observability for containerized model endpoints running on Kubernetes clusters. Troubleshoot and resolve operational issues as they arise.

Data Integration: Collaborate with data engineering teams to ensure clean, reliable data pipelines (such as Medallion architectures) seamlessly feed into machine learning models.

Engineering Best Practices: Write clean, modular, and testable code (primarily in Python) while adhering to version control best practices using Git.

Mentor, guide, and develop junior/aspiringMLOpsEngineeracross the organization.

Lead continuous career development and drive engineering excellence through performance reviews.

Qualifications& Requirements:

6+years of professional experience (orequivalentstrong academic/internship experience) inMLOps, Data Engineering, Software Engineering, or a related field.

3+ years of experience managing and scaling high-performingMLOpsor data platform teams, with a focus on career development, performance management, and technical mentorship.

Cloud ML Platforms: Hands-on experience with at least one major cloud ML platform. While Azure ML and Microsoft Fabric are preferred, experience with AWS SageMaker, Google Cloud Platform Vertex AI, or similar platforms is highly acceptable.

Programming: Strongproficiencyin Python for scripting, automation, and model deployment.

DevOps & Containerization: Familiarity with version control (Git), building CI/CD pipelines (e.g., GitHub Actions, Azure DevOps), and containerization ecosystems (Docker, Azure Container Registry, Kubernetes/AKS/ACS).

Foundational Knowledge: A solid understanding of the machine learning lifecycle, containerizedmicroservicesarchitectures, and fundamental software engineering principles.

Functional Skills:

Practical experience with as many of the following as possible:

Handles multiple competing priorities in a fast-paced, deadline-driven environment

Strong attention to details and excellent problem-solving skills

Ability to work in a collaborative team environment

Highly innovative, adaptable, and self-directed

Results-oriented with a delivery focus

Presentation skills: Ability to communicate technical topics to businessaudience.

Be able to collaborate across other levels of the organization

Team player who can lead a discussion to defined outcomes

Effective Communication

Pursuing Innovation

What We Can Do for You:

Innovation & Technology:The ability to work with an award-winning team that is on thecutting edgeof innovation.

Exposure to World Class Leaders:Availability to global technology leaders that will expand your network and exposure you toemergingtechnologies and techniques.

Agile Work Environment:We embrace agile with management that believes in removing barriers, so you are empowered to experiment,iterateand innovate.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: coke
Position Id: R-144420
Posted 19 days ago

Company Info

About The Coca-Cola Company

On May 8, 1886, Dr. John Pemberton brought his perfected syrup to Jacobs' Pharmacy in downtown Atlanta, where the first glass of Coca‑Cola was poured. In its first year, about nine Coca-Cola drinks were served per day.

Today, The Coca-Cola Company, with numerous brands sold across more than 200 countries and territories, serves 2.2 billion drinks per day. We own 32 billion-dollar brands across several beverage categories worldwide. Our global portfolio of beverage brands includes the following:

• Sparkling Soft Drinks: Coca-Cola, Diet Coke/Coca-Cola Light, Coca-Cola Zero Sugar, Fanta, Fresca, Schweppes (owned by The Coca-Cola Company in certain countries other than the United States), Sprite and Thums Up
• Water, Sports, Coffee and Tea: Aquarius, Ayataka, BODYARMOR, Ciel, Costa, Crystal, Dasani, Fuze Tea, Georgia, glacéau smartwater, glacéau vitaminwater, Gold Peak, I LOHAS, Powerade and Topo Chico
• Juice, Value-Added Dairy and Plant-Based Beverages: Core Power, Del Valle, fairlife, innocent, Maaza, Minute Maid, Minute Maid Pulpy, Santa Clara and Simply

Our strong and stable bottling and distribution system helps us capture growth by manufacturing, distributing and selling existing, enhanced and new innovative products to consumers throughout the world.

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