Kraft Heinz is looking for a Senior Principal Scientist, R&D – Analytical Sciences to lead the design of experiments, root cause analysis studies, and build shelf life kinetic and predictive models. This role will translate lab and process data into actionable product development strategies, shelf life optimization protocols, and product risk insights. The position also serves as the Data SME for analytical data processing, analysis, and modeling to extract key business insights using advanced data application software, AI technology, and statistical principles for R&D and field-to-shelf business decisions.
Requirements
- Highly skilled in design of experiment for complex food systems using techniques like Full Factorial, Fractional Factorial and Response Surface Methodologies.
- 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.
- Develop and validate kinetic and predictive models (Arrhenius, nonlinear regression, Bayesian hierarchical models, survival analysis) to predict quality attrition and failure probability across shelf life and storage conditions.
- 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.
- Automate data pipelines, reproducible analysis (R, Python), and maintain documentation and model governance.
Responsibilities
- leading the design of experiments, root cause analysis studies, and build shelf life kinetic and predictive models
- serve as the Data 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
- 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.
- Automate data pipelines, reproducible analysis (R, Python), and maintain documentation and model governance.
- Work with IT/Data Engineering to deploy models where needed and ensure data governance.
- Hands-on lab experience using cutting-edge food and beverage analytical instrumentations This involves expertise in the entire workflow, from knowledge of sample preparation and data acquisition to processing, statistical analysis, and compound characterization in complex food systems.
Other
- Remote, Hybrid or Onsite: Hybrid
- 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.
- Demonstrate broad understanding of food formulations, packaging, processing and analysis.
