Senior Manager, Data Science

Location(s):

United States of America

City/Cities:

Atlanta

Travel Required:

00% - 25%

Relocation Provided:

No

Job Posting End Date:

July 14, 2024

Shift:

Job Description Summary:

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, continu