$149,500 – $249,300
Listed on General Mills’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
A senior technical leader who designs and deploys enterprise AI solutions across supply chain and related domains, translating complex business problems into production-grade systems and mentoring the broader data science organization. This role suits experienced data scientists with deep expertise in machine learning, optimization, and advanced AI techniques, who thrive in strategic partnership with business and engineering teams.
Our summary, not General Mills’s wording. The full posting is on their site.
Skills this role names
- Agile
- CI/CD
- Computer Vision
- LLMs (Large Language Models)
- Machine Learning
- Natural Language Processing
- Python
- Retrieval-Augmented Generation
- Statistical Modeling
- Version Control
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What they ask for
Required
- 10+ years in data science or applied analytics
- At least 3 years in Principal, Lead, or equivalent senior technical role
- Advanced degree in quantitative field (Data Science, Computer Science, Engineering, Statistics, Math, Operations Research, or related)
- Expertise in statistical modeling, machine learning, and optimization
- Hands-on experience architecting and deploying scalable AI/ML solutions on major cloud platform (preferably GCP)
- Production-grade model building and decisioning systems at scale
- Technical leadership experience setting direction and establishing standards
- Leading complex AI/ML programs across multiple teams
- Experience with unstructured data and advanced AI integrated into business workflows
- Strong communication skills explaining analytical concepts to technical and non-technical audiences
- Modern data science engineering practices (version control, code review, testing, CI/CD)
- Demonstrated mentoring and development of other data scientists
- Currently authorized to work in the United States on a full-time basis
Nice to have
- Deep experience applying data science and AI to Supply Chain domains (planning, logistics, manufacturing, sourcing)
- Leading solutions combining traditional modeling with LLMs, agentic AI, and RAG in production
- Large-scale data processing and modern stack components
- Evidence of thought leadership (internal forums, publications, open-source contributions)