Senior R&D Statistical Scientist: Data-Driven Innovator

General Mills, Inc.; Golden Valley, Northern (MN, KY); Hybrid; USD 111,000 - 185,000; Full time

Job summary

General Mills, Inc. in Golden Valley, MN, seeks a Sr. R&D Statistical Scientist (Statistician) to join the Data Science & Modeling team within ITQ. The role blends statistics, modeling, and programming to tackle product development, nutrition research, and quality challenges, driving data-driven decisions.

You will mentor statisticians globally, translate complex analyses into actionable insights, and collaborate with partners to scale analytics with Python, R, and cloud tools.

Qualifications

• Ph.D. in Statistics or Biostatistics or relevant field.
• 3+ years of work experience in a statistical scientist/analyst role.
• Proficiency in SQL and experience with BigQuery and Oracle.
• Experience with Python and R analytics.
• Strong communication and teaching skills for cross-functional partners.

Responsibilities

• Provide statistical consultation in experimental design and analysis to scientists and engineers.
• Train, mentor, and coach other statisticians globally.
• Translate analyses into actionable insights and recommendations for business decisions.
• Develop statistical and machine learning models with Python, R, or other languages.
• Build and deploy analytics solutions with data pipelines for data-driven decisions.

Skills

Strong communication

Teaching

Mentoring

Statistical modeling

SQL

Education

Ph.D. in Statistics or Biostatistics or relevant field

Tools

BigQuery

Oracle

Python

R

Git

Job description

General Mills, Inc. in Golden Valley, MN, seeks a Sr. R&D Statistical Scientist (Statistician) to join the Data Science & Modeling team within ITQ. The role blends statistics, modeling, and programming to tackle product development, nutrition research, and quality challenges, driving data-driven decisions.

You will mentor statisticians globally, translate complex analyses into actionable insights, and collaborate with partners to scale analytics with Python, R, and cloud tools.