Expert Data Scientist (AI)

Nestle Operational Services Worldwide SA•Arlington, VA

5d•$140,000 - $196,000•Hybrid

About The Position

As the digital arm for the world's largest food and beverage company, Nestlé IT & Digital Americas harnesses the power of data, analytics, and innovative technology to deliver transformative solutions and business resiliency for Nestlé businesses and iconic brands from Purina® to Nescafé®. We’re innovators, strategic collaborators, value multipliers, and digital business leaders committed to delivering results that create meaningful experiences and drive value, enabling Nestlé to win in the marketplace. By joining, you become part of a 150-year legacy and a global team of 270,000+. We invest in our people—their growth, development, and sense of belonging. This shared unity and purpose is what motivates individuals to join, stay, and advance their careers within Nestlé. This position is not eligible for Visa Sponsorship. Position Summary Join Nestlé IT & Digital as an Expert AI Data Scientist supporting Nestlé USA (NUSA). You'll sit at the seam between business and technology, framing ambiguous business problems and then owning the AI solution end-to-end, from problem definition through adoption. This is a hybrid role, equal parts product manager and technical engineer. You won't just build models; you'll direct AI agents, build the verification and workflow scaffolding that lets a product team ship reliably, and leave behind reusable assets that make the next project easier. Success is measured by durable impact and adoption, and as agents and the surrounding tooling keep reinventing themselves, you'll help shape how NUSA scales AI responsibly.

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, or a related field
7+ years of experience partnering with cross-functional stakeholders to translate business needs into technical solutions and drive adoption
5+ years with a demonstrated track record of building and shipping AI/ML solutions that real users adopted
3+ years of experience deploying and scaling solutions at enterprise scale, including MLOps and cloud platforms such as Databricks and Snowflake
3+ years of experience delivering production solutions with emerging technologies, advanced data and automation capabilities, or machine learning, with a recent focus on AI, GenAI, LLMs, agentic workflows

Nice To Haves

Master's or PhD in Computer Science, Engineering, Mathematics, Statistics, Data Science, or a related discipline is preferred
Experience directing AI agents or agentic workflows to do substantive work, not just single-prompt usage, is preferred
Experience driving AI concepts from idea to enterprise-scale adoption, ideally in consumer products, CPG, Supply Chain, or Commercial environments is preferred
Strong hands-on engineering fluency in Python (or similar) for building, deploying, and integrating AI solutions, including modern LLM and agent patterns such as prompt interaction, tool/function calling, retrieval, and handling non-determinism, is preferred

Responsibilities

Serve as a thought leader on emerging AI, GenAI, and agentic technologies, translating breakthrough capabilities into scalable applications aligned with Nestlé's business priorities and enterprise value
Partner with stakeholders to translate ambiguous business needs into clear, precise specifications, surfacing data requirements, tradeoffs, and failure modes, and act as an internal consultant who scopes problems, defines success criteria, and drives alignment across the lifecycle
Own AI applications end-to-end, from use-case concept and experimental design through industrialization, deployment, and adoption, staying accountable across the full lifecycle rather than a single phase
Orchestrate AI agents across parallel streams of work, turning repeated tasks into reusable workflows the broader team can leverage, and incorporate agents into new and existing solutions as the technology landscape evolves
Design evaluation frameworks, conformance checks, and monitoring that validate AI output against defined specifications before rollout, including detection of silent errors, and sustain solutions in production through agent-assisted diagnosis of data-quality and pipeline issues
Strengthen the team's collective capability by documenting decisions, learnings, and incidents in shared resources, and coach business users and teammates to elevate performance across projects
Partner across global and regional IT & Digital teams to co-create and scale AI solutions, navigating platform roadmaps and enterprise processes to secure approval for needed features and capabilities
Build solutions with security and resilience in mind, protecting sensitive data and safeguarding the critical business processes they touch, and anticipating failure and misuse so AI systems remain safe, trustworthy, and reliable in production