Principal D&T Data Scientist

COMPANY OVERVIEW We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one another and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.​ 
 JOB OVERVIEW:  The Principal Data Scientist position is a senior technical leader who strategizes enterprise-grade AI solutions, spanning agentic AI, NLP, optimization & machine learning, to unlock measurable value across the Supply Chain and aligned domains. By working as a strategic partner to Supply Chain and cross-functional leaders in Product and Engineering, this role translates 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 on a variety of AI platforms, 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 that accelerate high-quality solution delivery and responsible AI adoption. KEY ACCOUNTABILITIES:  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 primary 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, leveraging 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 and applications. Provide technical oversight across core data science methodologies—including statistical, machine learning, and optimization approaches, ensuring method selection, validation, and implementation are rigorous, fit-for-purpose, and consistent with AI standards. Partner closely 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, fully 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 to ensure transparency, reproducibility, and reuse across capabilities. 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 and patterns. Champion Responsible AI by ensuring privacy, security, and governance compliance;