Expert Commercial Data Scientist

Nestle Operational Services Worldwide SA•St. Louis, MO

9d•$133,000 - $188,000

About The Position

The Expert Commercial Data Scientist at Nestlé Purina supports enterprise-wide AI and machine learning use-case creation, deployment, and operationalization across critical business initiatives. The role combines technical depth with commercial impact to help build connected digital capabilities for reaching consumers across channels. It partners with commercial and marketing teams to address retail and direct-to-consumer engagement challenges and translate emerging AI technologies into measurable business results. The position advises brand, marketing, sales, and category leaders; develops and deploys advanced analytics and AI solutions for consumer-facing and go-to-market problems; operationalizes generative AI for marketing and commercial workflows; and guides AI model deployment, governance, and lifecycle practices. It also develops reusable frameworks and mentors junior data scientists while providing thought leadership on emerging technologies.

Requirements

Bachelor's degree in Data Science, Marketing Analytics, Applied Statistics, Economics, Computer Science, or a related field.
At least 3 years of experience advising senior business stakeholders, shaping ambiguous strategic problems, influencing decisions, and translating complex AI and analytical concepts into business outcomes.
At least 7 years of professional experience, including at least 5 years applying data science, advanced analytics, or machine learning to marketing, consumer, commercial, e-commerce, sales, or related customer-facing business problems.

Nice To Haves

Master's or PhD in Data Science, Applied Statistics, Marketing Analytics, Economics, Computer Science, or a related field, or an MBA.
Experience operationalizing AI solutions through AIOps/MLOps frameworks, model governance, and enterprise AI lifecycle management.

Responsibilities

Act as a trusted data science and AI advisor to brand, marketing, sales, and category leaders, helping identify high-value opportunities, frame ambiguous business problems, and translate strategic priorities into scalable AI and advanced analytics solutions.
Lead the design, development, validation, deployment, and adoption of advanced statistical, predictive, optimization, machine learning, and generative AI solutions for complex consumer-facing and go-to-market business problems.
Design and operationalize generative AI solutions, including RAG pipelines, AI agents, copilots, and multimodal AI applications, to support marketing and commercial workflows where appropriate.
Guide model deployment strategies, including AIOps/MLOps, monitoring, model governance, and lifecycle management.
Develop reusable frameworks, accelerators, and best practices to improve the scalability and maintainability of AI solutions.
Mentor junior data scientists and provide thought leadership on emerging technologies such as agentic AI, knowledge graphs, and autonomous decision-making systems.