About the Research Team:
The Research to Experimentation (RtE) function in Technical Innovation & Supply Chain (TI&SC) delivers scalable and impactful innovations in the areas of ingredients, packaging, and dispensing (package-less) that grow, sustain, and protect our business. The Flavor and Ingredients Research (FIR) team is part of RtE and creates a compelling consumer sensorial experience through flavor & ingredients.
Our team is researching and developing the most advanced science and technology in the beverage industry to help drive business related innovation and growth. We continuously leverage the external technology development into our research program. As Coca-Cola evolves the way we leverage data across different functions, the FIR team is evolving the way that ingredient research is done, more agile through digital transformation & AI.
Job Description Summary:
You will play a critical role in our research program in Global R&D, where you will be responsible for building dataset, developing advanced analytics and machine learning models across domains by digging into very valuable data generated from long time product development across our global R&D community. You will work closely with IT partners, project owners and business stakeholders to deliver impactful data science solutions and insight for research program directions. You will have the opportunity to do your best work every day and deliver disruptive innovation by tapping into new datasets, leveraging the latest cloud technologies, and being supported by a dedicated research team, robust analytics and TI&SC and IT organizations.
Critical Skills
Strong data science skills with ability to communicate and simplify complex data analysis into actionable, easy to understand insights. Strong ability to leverage advanced analytics to enable effective, data-based decision-making.
Strong communication skills (written & verbal) and strong data storytelling skills required. Proven ability to write concise, informative reports and verbally present complex technical information to non-technical audiences. Ability to listen to and influence those in less technical roles to act and invest in capabilities with compelling business cases.
Ability to translate strategy into action, using knowledge of current business processes & practices and evolving technology & data to develop tools and solutions.
Must be an effective influence manager capable to manage stakeholders and cross-functional partners.
A proven track record of turning complex business issues into simple and actionable recommendations.
Strong project management skills including knowledge of project management principles and the ability to apply the principles, tools and techniques to develop/plan, manage or execute projects or work plans to ensure successful completion (e.g., on time, within budget). Must have the ability to oversee multiple projects simultaneously.
Key Responsibilities:
Partner with business and technical stakeholders across the organization to translate challenging business problems into impactful data science solutions.
Collaborate with research scientists, project owners and business users to lead projects through the end-to-end data science lifecycle, including data wrangling, exploratory analysis, hypothesis testing, modeling, rapid prototyping, business validation/testing, and operational deployment.
Build dataset by digging, sorting, cleaning and appropriately formatting the intensive historical research data against the current research problem.
Apply a variety of advanced analytical techniques, including predictive modeling, machine learning, simulation, optimization, and time series analysis.
Leverage a diverse set of large structured and unstructured data to derive meaningful insights and information sets for modeling.
Communicate complex analytical work to a variety of technical and non-technical stakeholders including executive management such as the Chief Technical and Innovation Officer.
Maintain expertise and awareness of emerging cheminformatics and data science techniques, technologies, and potential business applications for ML/AI.
Build and maintain a robust library of data science solutions, reusable templates, algorithms and supporting code.
Explore and implement new methodologies, continuously improve operational efficiency, and support innovation agenda.
Analyze data using Cheminformatics, Data Science, and statistical principles, evaluate results, form conclusions, and implement process improvements/recommendations.
Lead benchmarking activities for key formats to understand competitive advantage and opportunities.
Stay connected with the industry and up to date on new consumer science, sensory research, and relevant cheminformatics/data science techniques.
Collaborate cross-functionally and manage multiple projects simultaneously. Strongly collaborate with different functions in RtE and other TI&SC functions as needed.
Minimum Requirements:
Master’s degree in an analytical field such as but not limited to Data Science, Computer Science, Applied Mathematics, or Computational Chemistry. 3 additional years of related experience beyond the minimum required may be substituted in lieu of a degree. PhD is preferred.
3+ years’ experience in using digital tools, working as a data scientist developing, optimizing, and deploying production models.
Demonstrated experience applying a range of statistical and modeling techniques including hypothesis testing, dimensionality reduction, supervised learning (classification and regression), unsupervised clustering, and forecasting.
Demonstrated experience, proficiency, and best practices within the python data science stack (Pandas, NumPy, scikit-learn, SciPy, Matplotlib/Seaborn) – 3+ years’ experience in a professional settling.
Demonstrated experience, proficiency, and best practices using deep learning frameworks/libraries such as PyTorch and HuggingFace for training, fine-tuning and inference with and without GPU acceleration.
Experience gathering, interpreting, and translating research and business requirements.
Strong aptitude for learning and applying new technologies related to Data Science.
Experience with code version control platforms like GitHub, GitLab or Azure DevOps.
Preferred Experience:
Experience working in science related projects: research and application.
Degree or proven experience working in projects in the field of Chemistry, Food Science, Biology, Food Engineering or Chemical Engineering.
Nice to Have Experience:
Experience working in the CPG industry.
Experience within the Cheminformatics space using libraries such as RDKIt and DeepChem to solve research and business problems
Experience searching out and implementing findings/code from scientific literature within the fields of Chemistry, Food Science, Biology, Food Engineering or Chemical Engineering.
What We Can Do For You
Purpose Driven: Purpose driven approach that empowers our people to protect the environment and communities we serve while delivering safe & quality products.
Global Connections: Allows you to develop, enhance and maintain global connections that allow us to move faster and learn from others.
Community of Belonging: We’re an organization that believes our ability to continually grow and build the right atmosphere where people feel safe and empowered, lets you bring your
SkillsInfluencing
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