Director, Data Science

Director, Data Science

Atlanta, GA

Director - Data Scientist, AI/ML and Molecular Discovery

Role Overview:

The Director, Data Scientist, AI/ML and Molecular Discovery, is a critical role within Flavor & Ingredient Research and Application (FIRA) and Research to Experimentation (RtE). The role will be responsible for setting the FIRA digital and AI strategy, providing system wide thought leadership in using AI/ML in discovery, and drive advanced data and AI initiatives to accelerate research and development initiatives.

The Flavor/Ingredient Research and Application (FIRA) team aims to develop and deploy cutting-edge research to drive business-related innovation and growth. We leverage the latest innovations in science and technology, including artificial intelligence, machine learning, and data science approaches, to analyze complex research data, discover new insights, and enable a deeper understanding of The Coca-Cola Company's ingredients and beverage systems.

• Propose and help to develop a comprehensive AI/ML strategy to enable and accelerate R&D initiatives across different functions within FIRA with measurable results.
• Leverage both internal and external expertise to direct internal model development, evaluating external AI opportunities, and to guide future AI-driven capabilities.
• Collaborate with different functions in FIRA to implement the strategy aligned with business objectives and priorities.

• Chemical property predictive models
• Virtual / in silico screening and lead optimization
• Generative AI for protein structure prediction co-folding (peptides, small molecules)
• De novo molecular design using generative chemistry

• Utilize advanced data analytics and AI strategies to optimize insights from biological, sensory, and clinical data.
• Guide and evaluate digital strategy and data management across FIRA.

• Collaborate across multiple disciplines - such as Biology, Chemistry, Sensory, Application, Analytical Sciences
• Partner with data scientists and engineers across TI&SC and Platform services
• Participate in company-wide AI initiatives and communities of practice to further the adoption AI and enable digital synergy across TCCC network

• Represent our data-driven research agenda to external parties and collaborators.
• Advance AI/ML research projects through external networks.
• Champion the development of Agentic AI frameworks with partners such as Microsoft, Accenture, CapGemini, etc.

• Business Acme: TCCC business understanding and system knowledge.
• Communication Skills: Ability to present complex scientific concepts and articulate business impact to both peers and senior leadership.
• Strategy Development and Innovation: Provide strategic recommendations to influence research direction and AI adoption as it relates to TCCC business priorities and long-term goals.
• Advanced Knowledge of Machine Learning: Familiarity with machine learning algorithms and techniques, such as supervised and unsupervised learning, neural networks, and deep learning. Ability to apply machine learning models to chemistry-related problems, including drug discovery, molecular property prediction, and biological function.
• Collaboration and Project Management: Manage research collaborations with CROs, academic labs, and research consortia. Collaborate and supple multiple functions.
• Strong Foundation in Computational Biology/Chemistry.
• Programming Skills: Proficiency in programming languages commonly used in cheminformatics and machine learning, such as Python, R, and Java. Experience with data analysis libraries and machine learning frameworks, such as NumPy, SciPy, Scikit-learn, TensorFlow, and PyTorch.
• Data Handling and Manipulation: Skills in data preprocessing, cleaning, and transformation to ensure high-quality input for machine learning models. Ability to work with large datasets.
• Analytical Thinking and Problem-Solving: Strong analytical skills to interpret complex chemical and computational problems. Creative problem-solving abilities to develop novel solutions in cheminformatics.
• Bioinformatics and Computational Biology Knowledge: Understanding biological data and systems, especially for applications in drug discovery and development.
• Leadership in Research: Ability to conduct research, interpret data analyses, and contribute to scientific literature. Excellent skills in communication and teamwork to collaborate with chemists, biologists, data scientists, and other stakeholders.

• Continuous Learning: Eagerness to stay informed about new technologies related to AI, ML, and Data Science and related fields. Willingness to learn new tools, methodologies, and technologies as the field evolves. Should possess a strong background in molecular biology and computational chemistry, and capable of translating research needs into data science solutions.

• PhD in the chemical or biological sciences, must have a strong data science component.
• 10+ years of experience in data science, with a focus on optimizing and deploying predictive models.
• Demonstrated experience applying diverse and adaptive modeling techniques including dimensionality reduction, supervised learning (classification and regression), graph neural networks, unsupervised clustering, language models, and generative AI.
• Experience gathering, interpreting, and translating research and business requirements
• Proven leadership ability - lead collaborative efforts and drive rational decision making when faced with ambiguity and with no or minimal provided direction.
• Demonstrated ability to communicate complex analytical concepts and results at multiple levels to both technical and non-technical audiences.
• Demonstrated ability to translate science to technical projects and execute the projects to deliver business results
• TCCC business understanding and system knowledge is a plus