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Senior Scientist (Process Engineer – Data Scientist), Research & Development-Frozen Handheld and Spreads

The J.M. Smucker Co.
Columbus, OH
Full-time

Your Opportunity as a Senior Scientist (Process Engineer Data Scientist), Research & Development-Frozen Handheld and Spreads

In this role you will be responsible for leveraging the use of data science tools and techniques to develop and make inferences on data from process systems.

You will need to develop expertise in manufacturing processes such as baking, dough sheeting, mixing, slicing, depositing, and other process systems associated with the business to enable the use of quantitative / statistical / machine learning techniques.

These tools will be used to meet business goals related to fundamental process understanding, process capability and manufacturing efficiency.

This role will actively work with senior team members to develop the appropriate goals that drive business results. In addition, you will bring methods of analyzing and displaying large sets of data to both the technical community and our business leaders.

This role will lead the development of the connection between the process engineering discipline and the data science discipline for our business area.

To be successful in this role you will need a strong foundation in process engineering that demonstrates your experience in applying engineering principles to solve complex technical problems as well as a background in data science.

Location : Orrville, OH Corporate Offices (Estimated 50% Hybrid Environment to accomplish goals of the team and anticipated up to 30% Travel)

In this role you will :

  • Lead in the use of data science tools and techniques to develop and make inferences on data from process systems. This includes identifying the key process inputs and correlating them to key outputs which result in the development of our fundamental process control understanding for both existing process and new processes.
  • Develop and contribute to predictive modeling techniques as applied to manufacturing processes.
  • Build the organization’s technical depth in statistical data analysis and methods.
  • Develop expertise in Consumer manufacturing processes focused on the technologies used in our facilities which enable a deeper understanding of the data being analyzed.
  • Provide technical leadership for process development through the lens of Data Science for new products, including design of pilot plant (PRL) experiments, creation of test plans for plant trials and scale-up from the pilot scale to manufacturing and our Commissioning, Qualification and Verification process for product / process launches.
  • Design data-driven solutions to enhance analytical capabilities helping to correlate analytical measures to key product and process parameters.
  • Determine and recommend the highest value areas to study which bring the greatest impact to our business. Impact to our business is measured both from the consumer need perspective and the manufacturing efficiency perspective.
  • Identifies opportunities and advocates for implementation of best practices in the discipline of data science, focusing on its application to process systems. .
  • Partner with the Smucker Information Services Data Science (IS) team on several aspects of this discipline including the creation and maintenance of Data Science learning paths allowing the organization to keep up with current trends in the discipline and in shaping the company's machine learning strategy
  • Guides other team members and developers, working with our IS data science team to set up sustainable data pipelines for modelling initiatives.

Understands best practices in the Data Engineering space and sees impact on Data Science.

  • Can explain advanced concepts specific to model training and is capable of leading others through the process. Helps the team and stakeholders understand scope and limitations of models.
  • Coach and mentor early-career food technologists and process engineers as part of our Basic Belief and Commitment to Each Other philosophy.
  • Support the department through leadership of QA and / or HS&E Key Elements.
  • Embrace and actively participate in company’s inclusion, Diversity and Equity (ID&E) corporate initiative.

The Right Place for You

We are bold, kind, strive to do the right thing, we play to win, and we believe in a strong community that thrives together.

Our culture is rooted in our , and we believe in supporting every employee by meeting their physical, emotional, and financial needs.

What we are looking for :

Minimum Requirements :

  • Bachelor’s Degree or higher in Engineering (Chemical preferred)
  • Practical experience applying data science techniques in a manufacturing environment
  • Minimum of ten (10) years of relevant experience in Data Science, Engineering and / or Research & Development
  • With at least 2+ years of hands-on experience developing and applying Statistical / ML predictive methods or comparable experience
  • Ability to communicate difficult technical concepts, and the ability to collaborate across functional teams to achieve shared goals and objectives.
  • Strong critical thinking and complex problem solving
  • Ability to apply statistical thinking and decision making
  • Ability to work independently in complex situations

Additional skills and experience that we think would make someone successful in this role :

  • Master’s degree or higher in Engineering (Chemical preferred) and a BS degree in Data Science or closely related field
  • Experience with data science application to new or existing manufacturing processes in a beverage or food related field
  • Well-versed in R and / or Python, with a deep understanding of relational data structures and SQL
  • Demonstrated project management skills through process / equipment qualification
  • Strong background in applying engineering principles & critical thinking to solve complex technical problems.
  • Deep understanding of what data science algorithms and approaches to apply to different situations.

Learn more about working at Smucker :

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