Junior Machine Learning Engineer

Summary: 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   Junior Machine Learning Engineer, 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,   Techni cal   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 .   Visualiz e   and interpret   data and   creat e   reports   and actionable insights .     Communicate complex analytical work to a variety of technical and non-technical stakeholders .   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   or other quantitative   discipline .     Experience gathering, interpreting and translating business requirements .   2 + years ’ experience with   analytical and programming languages and packages, such as Python, R , and SQL .   Able to understand various data structures and common methods in data   transformation.   Knowledge and e xperience   applying a range of statistical, modeling, and mathematical optimization techniques including hypothesis testing, dimensionality reduction, Mixed-Integer Programming (MIP), supervised learning (classification and regression), Bayesian modeling, forecasting, and unsupervised clustering and putting solutions into production.   Strong aptitude for learning and applying new technologies related to Data Science and Data Management .   Demonstrated ability to communicate complex analytical concepts and results at multiple levels to both technical and non-technical audiences .   Experience with code version control platforms like GitHub, GitLab or Azure DevOps .     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 business audience.   Be able to collaborate