Sr. Data Scientist

General Mills

We serve the world by making food people love

Do you find that you see patterns or opportunities that others don’t see? Do you enjoying asking questions and analyzing data to deepen your knowledge? Do you like to challenge historical assumptions and recommend new ways to drive action based on data driven insights? Do you like to find the best way to tackle a problem and share the approach with others?

General Mills is seeking a Sr. Data Scientist to join an established and growing data science team in the Global Business Solutions shared services organization. Our team is the Data Science center-of-excellence for General Mills, tasked with serving functional data science and analytics teams through the whole Fortune 500 organization. Some of our projects include demand forecasting, text classification, operational analytics, and pricing optimization. We are looking for candidates who enjoy solving new, difficult problems, working with diverse internal business partners, and who can deliver continual improvement in both themselves and those they work with.

  • Solve business problems
  • Develop novel ways to help business partners meet objectives utilizing cutting edge techniques and tools
  • Advocate and educate on the value of data driven decision making focusing on the “how and why” of solving problems
  • Lead analytic approach within cross-functional projects
  • Create exemplary analytic data products
  • Utilize machine learning on the General Mills Hadoop Data Lake to create repeatable, dynamic & scalable models
  • Engineer features by using your business acumen to find new ways to combine disparate data sources
  • Share your passion for Data Science
  • Curate and connect external data sets for broad enterprise-wide analytic usage
  • Identify and develop long-term data science processes, frameworks, tools, and standards
  • Collaborate, coach, and learn with a growing team of experienced Data Scientists

To apply for this job please visit careers.generalmills.com.

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