Principal Scientist, R&D – Analytical Science

Job Description

Principal Scientist, R&D – Analytical Science

ABOUT 

This Principal Scientist position in the Food Engineering Division within Analytical Sciences is located at our Glenview, IL Kraft Heinz Innovation Center. This is an ideal opportunity for a scientist passionate about leading the design of experiments, root cause analysis studies, and kinetics studies encompassing, but not limited to, product quality and shelf-life testing. This position will also serve as the SME for analytical (example: linking chemistry and sensory) data processing, analysis and modelling to elucidate key business insights by leveraging advanced data application software, AI technology and statistical principles for R&D and field-to-shelf business decisions. The position emphasizes cross-functional holistic problem solving with R&D, Product Development, Quality, Operations and Factory personnel to identify needs and develop competitive-edge capabilities advancing KH agenda for a wide range of leading food products. 

RELATIONSHIPS (EXTERNAL AND INTERNAL): 

• Will collaborate with internal clients including R&D, Product Development, Quality, Operations and Factory personnel. 

• Will collaborate and represent KH well when working with external professionals from accredited consortiums and universities 

• Will interact with instrument and software vendors, ingredient suppliers, co-manufacturing facilities and external lab partners. 

QUALIFICATION REQUIREMENTS: 

• Highly skilled in design of experiment for complex food systems using techniques like Full Factorial, Fractional Factorial and Response Surface Methodologies. 

• Apply statistical models with examples like Minitab, SAS, R, Python and MATLAB to food kinetic data to predict changes in quality and optimize processes 

• Deep knowledge around the fundamentals of kinetics such as substance structure-function, food matrix mechanisms and rates of reactions in the areas of enzymatic browning, lipid oxidation, discoloration, fermentation and others.  

• Process and interpret data for R&D and cross-functional projects effectively using approaches such as PCA, PLS and regression tree 

• Translate complex data or large data set into effective data visualization and presentation using Tableau or other data visualization tools to deliver business insights to peers, senior leaders and stakeholders. 

• Demonstrate