Senior Director, Machine Learning Advanced Analytics

Coca-Cola; Georgia; On-site; USD 180,000 - 240,000; Full time

Job summary

The Coca-Cola Company’s Technology organization is undergoing a digital transformation to connect products to customers worldwide using world-class technology. This role focuses on leading ML/AI initiatives, working with cross-functional teams, and delivering end-to-end data science solutions from ideation through production and monitoring.

You will mentor data scientists, drive engineering excellence, and collaborate with executive stakeholders to scale ML across Marketing, Finance, and Supply

Qualifications

• Bachelor's or master's degree in a quantitative field; Ph.D. preferred.
• 10+ years applying statistical, modeling, and optimization techniques including MIP and forecasting.
• 5+ years managing and scaling high-performing ML teams.
• Experience translating business requirements into data-driven solutions.

Responsibilities

• Collaborate with cross-functional teams to understand objectives.
• Translate requirements and develop ML/AI models for diverse use-cases.
• Partner with product teams to ensure seamless solution integration.
• Develop end-to-end AI/ML solutions from ideation to monitoring.
• Mentor data scientists and drive engineering excellence.

Skills

Machine learning

Data science

Python

SQL

R

Leadership

Cross-functional collaboration

Education

Bachelor's or Master's in a quantitative field

Ph.D. preferred

Tools

Azure Synapse

Databricks

Cosmos DB

GitHub/GitLab/Azure DevOps

Job description

Job Description 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.

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.
• Partner with product teams and incorporate experience in product design to ensure seamless solution integration.
• Leverage a diverse set of large structured and unstructured data to derive meaningful insights and information sets for modeling .
• Develop , man age, and maintain end-to-end ( E2E) AI/ML solutions from ideation, production, and ongoing monitoring
• Communicate complex machine learning 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.
• Develop and m aintain 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 AI and Machine Lear n ing
• Mentor, guide, and develop junior/aspiring data scientists across the organization .
• Lead continuous career development and drive engineering excellence through performance reviews.
• Manage vendor selection and oversee external vendors' delivery and work items.

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 disciplines . Ph.D. preferred.
• 10+ years' experience 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.
• 5+ years of experience managing and scaling high-performing machine learning teams.
• Experience gathering, interpreting and translating business requirements, with a preferred background driving product innovation or solving complex supply chain and operational challenges.
• Proficient 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.
• Demonstrated experience in large-scale data wrangling with relational databases and/or Spark.
• Demonstrated experience building end-to-end (E2E) data science and analytic solutions from ideation, production, and ongoing monitoring.
• Demonstrated experience coordinating with cross-functional teams in completion of E2E solutions.
• Demonstrated experience with the Microsoft Azure analytics stack (Cosmos DB, Azure Synapse, Azure ML, Databricks)
• 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 , including senior executive stakeholders
• Be able to collaborate across other levels of the organization
• Team player who can lead a discussion to defined ou