R&D Manager, Industrial Statistics & Experimentation - Golden Valley, MN

General Mills•Golden Valley, MN

4d•$126,700 - $190,100

About The Position

We’re hiring an R&D Manager of Industrial Statistics and Experimentation to lead a team of 5 statisticians and data scientists within our global R&D organization. This is a player/coach role: you’ll guide and develop people, set standards for experimentation, and personally lead high-impact projects that accelerate product and process development. Beyond leading your team, you will be a key influencer across the R&D organization. You’ll be a core partner to Product Development, Process Development, Quality, and Operations, using your credibility and business acumen to embed statistical rigor in how we innovate, design experiments, and make decisions that will drive us to more efficient and effective R&D outcomes. Success in this role requires a leader who can drive results through technical expertise and partnership.

Requirements

Master's Degree in Statistics, Applied Statistics, Data Science, Industrial Engineering, or a related quantitative field
8+ years of applied / Industrial statistics experience in R&D, product/process development, or an industrial setting.
2+ years of people leadership experience, with a demonstrated ability to develop talent and manage team performance.
A strong track record of influencing in a matrixed organization.
Demonstrated, hands-on expertise in Design of Experiments (DOE) and applied modeling (ANOVA/regression/GLM; mixed models).
Proficiency with common statistical tools such as JMP and/or Minitab, plus R or Python

Nice To Haves

Ph.D. in Statistics, Applied Statistics, Data Science, Industrial Engineering, or a related quantitative field
Experience working in a consumer packaged goods or food manufacturing organization
Experience designing or analyzing sensory or consumer studies
Experience building reusable templates, automated analysis workflows, or lightweight tools/dashboards
Six Sigma Black Belt or Master Black Belt

Responsibilities

Lead, Coach, and Influence
Manage and develop a high-impact team: Lead, coach, and inspire your team through clear priorities and strong operating rhythms. Use General Mills’ talent processes to manage performance, develop skills, build long-term career growth, and foster a culture of continuous learning and innovation
Partner to Drive ITQ results: Partner across R&D and leverage your statistical expertise and business insight to influence technical strategy and decision-making in a matrixed environment to accelerate product development and improve product robustness
ITQ Influencer: Builds trust and alignment through credibility and clear communication, driving decisions without direct authority.
Set clear standards for engagement: Proactively establish and communicate clear ways of working for your team, ensuring team members know how to engage effectively with stakeholders to get the best results and build strong partnerships across ITQ.
Own R&D Experimentation Excellence (DOE is central)
Lead end-to-end Design of Experiments strategy: Guide the team on full-cycle experimentation, from screening and optimization to robustness and confirmation.
Select practical, fit-for-purpose designs: Choose the right experimental approach under real-world constraints (e.g., limited runs, pilot capacity, cost, split-plot designs).
Standardize experimentation best practices: Own and promote the use of experiment charters, clear decision rules, and consistent analysis and reporting standards.
Deliver Decision-Ready Analytics
Apply and guide advanced modeling: Oversee and apply approaches including ANOVA/regression/GLM and mixed models, ensuring sound diagnostics and interpretation.
Solve complex, correlated problems: Use multivariate methods (e.g., PCA/PLS) to uncover the true drivers of product and process performance.
Translate findings into action: Convert complex statistical findings into clear, actionable recommendations for cross-functional partners—what we learned, what it means, and what we do next to drive meaningful impact
Build Capability Across R&D
Train and coach R&D teams: Improve DOE literacy and interpretation skills across the organization through targeted training and coaching, fostering a data-driven culture within R&D.
Create reusable assets: Develop templates, playbooks, and analysis scripts that scale learning, improve consistency, and drive efficiency
Strengthen data and measurement discipline: Proactively partner with teams to improve data quality and measurement systems (repeatability, method readiness), ensuring analyses are traceable and reproducible.