Location: Mt. Sterling, IL or Chesterfield, MO
Department: Human Resources
Reports To: Vice President – Human Resources
Your Role: Research and analyze internal and external environmental data and provide recommendations based on
the data to achieve company and departmental goals. Also produces insights to help drive business strategies
through the use of advanced statistical modeling.
-Analyze employee and applicant testing and other human capital data.
-Analyze bi-annual employee survey data. Analyze data from other company departments.
-Utilize mathematical models in order to perform hypothesis testing.
-Applies lean thinking and tools to identify and eliminate waste in all areas of the position.
Travel – Occasional overnight travel of up to 1-2 nights per month for conferences or meetings. Must have
ability to travel independently as needed, without restriction by all modes of transportation, including car, plane,
What Can Dot Offer You?
As a family-owned and -operated company since 1960, Dot Foods has created a strong family culture within
the business. As a vital part of that family unit, we want to ensure you feel included and respected for any
differing ideas. We appreciate those opinions and count on them to make us successful. In addition to an
inclusive working environment, we will provide you with:
- A friendly working environment
- Highly competitive compensation and benefits package
- Significant advancement opportunities
We Need You To Have:
- Master’s degree in a quantitative discipline or
equivalent Dot Foods’ experience.
- Proven background in applied mathematics and
advanced statistics including regression analysis,
analysis of variance, correlations, and linear algebra.
- Ability to manage multiple tasks and meet critical
- Ability to work independently with multiple internal
company departments and locations.
- Experience in writing applied dissertation results
We’d Like You To Have:
- Experience in variable mapping across
- Experience in data warehouse technologies
such as Teradata.
- Proficiency in Data Science, quantitative
analytics, forecasting and predictive analytics,
multivariate testing and optimization
- Proficiency in the use of statistical packages
such as SPSS, Python, R, Cognos or Weka.