Senior R&D Statistical Scientist & Modeling Innovator

General Mills; Minneapolis (MN); On-site; USD 111,000 - 185,000; Full time

Benefits offered by this job

Total Rewards package

Health benefits

Annual incentive program

Job summary

General Mills in Minneapolis seeks a Sr. R&D Statistical Scientist to join the Data Science & Modeling team within ITQ. You will blend statistics, mathematics, and technology to transform data into actionable insights for product development, consumer testing, nutrition research, and quality.

You will mentor statisticians globally, translate analyses into business recommendations, and build models with Python or R in a data-rich environment with cloud-based data pipelines.

Qualifications

• Ph.D. in Statistics or Biostatistics or a related field.
• Experience applying statistics to product development, quality, or nutrition research is highly desirable.
• Strong communication and teaching abilities; ability to train and mentor colleagues.

Responsibilities

• Collaborate with R&D teams to solve problems using data across product development, quality, nutrition, and consumer research.
• Provide statistical consultation on experimental design and analysis for scientists and engineers.
• Develop statistical and machine learning models using Python, R, or other tools; scale analytics on cloud platforms.

Skills

Statistical modeling

Data analysis

Teaching/coaching

Communication

Cross-functional collaboration

Education

Ph.D. in Statistics or Biostatistics or relevant field

Tools

SQL

BigQuery

Oracle

R

Python

Git

Google Cloud Platform (GCP)

Job description

General Mills in Minneapolis seeks a Sr. R&D Statistical Scientist to join the Data Science & Modeling team within ITQ. You will blend statistics, mathematics, and technology to transform data into actionable insights for product development, consumer testing, nutrition research, and quality.

You will mentor statisticians globally, translate analyses into business recommendations, and build models with Python or R in a data-rich environment with cloud-based data pipelines.