Principal D&T Data Scientist

We exist to make food the world loves. Our company prioritizes being a force for good, expanding learning, exploring new perspectives, and reimagining possibilities. We look for bold thinkers with big hearts who challenge one another and grow together to become the undisputed leader in food.

About the role

The Principal Data Scientist is a senior technical leader who strategizes enterprise-grade AI solutions—spanning agentic AI, NLP, optimization, and machine learning—to unlock measurable value across the Supply Chain and aligned domains. This role partners with Supply Chain, Product, and Engineering leaders to translate complex business requirements into rigorously framed analytical problems and robust, production-grade decisioning systems. The Principal Data Scientist shapes and governs the end-to-end AI architecture and strategic roadmap, ensuring AI capabilities are secure, scalable, and aligned with General Mills' technology strategy. They elevate the broader Data Science community through technical mentorship and leadership in AI/ML best practices.

Responsibilities

• Lead, design, and execute novel, end-to-end AI solutions and systems that help business partners achieve strategic objectives through advanced analytics, modeling, and optimization, with a focus on complex Supply Chain decisioning.
• Partner with data science leadership, engineering, AI platform teams, and business stakeholders to define, prioritize, and deliver production-grade AI/ML products and services using best-in-class tools, frameworks, and cloud-native architectures on GCP.
• Provide technical leadership through strong business partnership, challenging assumptions, offering alternate architectural patterns, and making informed trade-offs between complexity, performance, cost, and long-term maintainability.
• Lead the reference architecture, design, and implementation of LLMs, NLP, and computer vision-driven solutions, owning patterns for problem framing, data curation, model lifecycle, and integration with core enterprise platforms.
• Provide technical oversight across core data science methodologies—including statistical, machine learning, and optimization approaches—ensuring method selection, validation, and implementation are rigorous and fit-for-purpose.
• Partner with AI Leadership, ML Engineering, and business stakeholders to define and evolve the architecture for agentic AI and retrieval-augmented systems, establishing standards, guardrails, and reusable components.
• Own the creation and operationalization of production-ready, scalable AI platforms, services, and models that provide real-time or near-real-time insights and decisions, aligned with General Mills' technology standards for security, reliability, observability, and lifecycle management.
• Provide technical leadership for analytical solution design and experimentation through hypothesis-driven approaches, robust evaluation strategies, and clear error taxonomies, with strong documentation and governance.
• Serve as a key member of the Data Science leadership team, shaping technical strategy, multi-year capability roadmaps, architectural standards, and operating practices that scale AI impact across the enterprise.
• Coach and develop data scientists and adjacent talent through deep technical reviews and mentoring on advanced AI concepts, domain best practices, and effective use of shared platforms.
• Champion Responsible AI by ensuring privacy, security, and governance compliance; proactively identifying and reducing model risks and embedding responsible AI principles into architecture, processes, and user experiences.
• Act as an internal and external thought leader on AI strategy, architecture, and data science, representing the Digital and Technology organization in forums, communities of practice, and key stakeholder engagements.

Requirements

• 10+ years of experience in data science or applied analytics, with ownership of end-to-end solutions from problem framing through production and measurable business impact, including at least 3 years in a Principal, Lead, or equivalent senior technical level.
• Advanced degree in a quantitative field (Data Science, Computer Science, Engineering, Statistics, Math, Operations Research, or related).
• Strong expertise in core data science methodologies (statistical modeling, machine learning, optimization) and their practical application to complex business problems.
• Hands-on experience architecting and deploying scalable AI/ML solutions on a major cloud platform (preferably GCP).
• Proven track record of building and operating production-grade models and decisioning systems at scale, including monitoring, performance management, and lifecycle governance.
• Demonstrated technical leadership setting technical direction, establishing standards, and influencing architecture and platform decisions.
• Experience leading complex AI/ML programs across multiple teams, with a strong grasp of project/program management fundamentals (roadmaps, prioritization, risk/dependency management).
• Experience with unstructured data and advanced AI (e.g., LLMs, NLP, computer vision) integrated into business workflows and applications.
• Strong communication skills, with the ability to clearly explain analytical concepts, results, and trade-offs to both technical and non-technical stakeholders.
• Proficiency with modern data science engineering practices: version control, code review, testing, CI/CD for models, and agile delivery.
• Demonstrated ability to mentor and develop other data scientists, leading by example on modeling rigor, experimentation, and documentation.
• Proven ability to stay current on evolving AI/ML technologies and to anticipate, evaluate, and advocate for appropriate adoption within the enterprise.

Preferred Qualifications

• Deep experience applying data science and AI to Supply Chain domains (e.g., planning, logistics, manufacturing, sourcing).
• Experience leading solutions that combine traditional modeling (predictive/prescriptive analytics, optimization) with newer paradigms (LLMs, agentic AI, RAG) in production.
• Exposure to large-scale data processing and modern stack components.
• Evidence of thought leadership in data science (e.g., internal forums, publications, or open-source contributions).

International relocation or international remote working arrangements (outside of the US) will not be considered. Applicants must be currently authorized to work in the United States on a full-time basis; General Mills will not sponsor work visas for this position.

Pay

The salary range for this position is $149,500 - $249,300 annually. Pay is determined by factors including education, skills, work experience, and certifications. Beyond base salary, General Mills offers a competitive total rewards package focusing on overall well-being, including health benefits, retirement and financial wellbeing, time off programs, wellbeing support, and perks. Eligible employees may participate in an annual incentive program based on individual and organizational performance.