Machine Learning Architect 1

The Coca-Cola Company’s Technology organization is in the midst of a digital transformation that allows our employees to use world class technology to connect our products to our customers all over the world. This journey is a very exciting time for Coca-Cola and our employees are big contributors to our Success and Growth. Our large scale and complex environment offers an incredible opportunity to address challenges, enable innovative solutions to make a difference for our customers. 

As a Machine Learning Architect 1 (Individual Contributor), you will embark on a journey of leveraging vast 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 strategy across the organization. This is an exciting opportunity to grow in your career in data science and analytics within a supportive and innovative environment. 

What You’ll Do for Us: 

• Collaborate with cross-functional teams to understand business requirements and objectives. 

• Translate business requirements by incorporating data and develop ML and AI algorithms to produce actionable insights for various functional areas and use-cases, including Marketing, Finance, Technical Innovation and Supply Chain (among others) across the Globe. 

• Leverage a diverse set of large structured and unstructured data to derive meaningful insights and information sets for modeling. 

• Visualize and interpret data and create reports and actionable insights.  

• Communicate complex analytical work to a variety of technical and non-technical stakeholders, including executive management. 

• Partner with ML OPS to scale and operationalize ML and AI use-cases. 

• Maintain technical documentation in accordance with the agreed standards. 

• Build and maintain a robust library of data science solutions, reusable templates, algorithms and supporting code.  

• Leverage CI and CD principles to automate and improve repeatability of deployments. 

• Keep abreast of industry trends and developments in data science and analytics. 

Qualifications & Requirements: 

• Bachelor’s or Master’s degree in a quantitative field, such as Data Science, Statistics, Computer Science, Economics, Finance, Mathematics, Operations Research or other quantitative discipline.  Ph.D. preferred. 

• Experience gathering, interpreting and translating business requirements. 

• Proficient