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Expert Data Scientist

Job in St. Louis, Saint Louis, St. Louis city, Missouri, 63105, USA
Listing for: Nestlé S.A.
Full Time position
Listed on 2026-07-19
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 130000 - 188000 USD Yearly USD 130000.00 188000.00 YEAR
Job Description & How to Apply Below
Location: St. Louis

Position Summary

Digital Transformation is at the center of all that we do. With data-driven innovators passionate about making a difference in the lives of pets, we create cutting-edged digital business models that solve complex problems. You’ll be at the forefront of digital advancements as they happen in real time, as well as ensure we remain a leader and innovator in the pet care category.

Have a hand in making a lasting impact within our long-standing history.

As an Expert Data Scientist at Nestlé Purina, you’ll support enterprise-wide AI and machine learning use case creation, deployment, and operationalization across critical business initiatives that drive significant value and transformative outcomes. This role sits at the intersection of technical depth and commercial impact, helping build the connected digital space that powers how we reach consumers across channels. You’ll bring a consumer lens to your work, partnering with commercial teams to solve challenges across retail and direct consumer engagement, and translating emerging AI technologies into measurable business results.

Responsibilities
  • Lead the development and deployment of advanced machine learning, optimization, and AI solutions to solve complex business problems across the commercial organization
  • Design, train, evaluate, and deploy scalable predictive and Generative AI models for enterprise and consumer-facing applications
  • Build and operationalize LLM-based solutions including retrieval augmented generation (RAG) pipelines, AI agents, copilots, and multimodal AI applications
  • Partner with business and commercial leaders to translate strategic priorities into AI solutions and drive adoption across retail and consumer channels
  • Guide model deployment strategies including AIOps/MLOps, monitoring, model governance, and lifecycle management
  • Develop reusable frameworks, accelerators, and best practices that 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
Requirements
  • Bachelor’s degree in Data Science, Applied Statistics, Mathematics, Computer Science, or a related field
  • 7+ years of professional experience, with 5+ of those years in data science, advanced analytics, and machine learning
  • 5+ years of experience with machine learning algorithms and frameworks (e.g., Tensor Flow, scikit-learn) for predictive modeling and deploying AI solutions in a production environment
  • 3+ years of experience in Python/SQL for advanced analytics, data engineering, and model development
  • 2+ years of experience designing, fine-tuning, evaluating, and deploying LLM-based applications for various data science use cases
  • 2+ years of experience with cloud computing platforms (e.g., Azure, AWS, GCP) and production AI system design
Other (Preferred)
  • Master’s or PhD in Data Science, Applied Statistics, Mathematics, Computer Science, or a related field (or an MBA) is preferred
  • Experience partnering with Marketing, Sales, and Consumer Insights teams to design AI-enabled workflows across areas such as campaign optimization, consumer engagement, pricing and promotion analytics, or digital commerce is preferred
  • Knowledge of database systems, data warehousing, and distributed computing frameworks (e.g., SQL, No

    SQL, Hadoop, Spark, or Ray) is preferred
  • Understanding of agentic AI, knowledge graphs, and autonomous decision‑making systems, along with expertise in GenAI models (e.g., GANs and diffusion models) and building LLM-based solutions such as RAG pipelines, copilots, and multimodal AI applications, is preferred
  • Experience operationalizing AI solutions through AIOps/MLOps frameworks, model governance, and enterprise AI lifecycle management, including responsible AI principles such as fairness, explainability, hallucination detection, and AI risk management, is preferred
Compensation and Benefits

The approximate pay range for this position is $130,000 to $188,000 per year. Final compensation may vary based on factors including but not limited to knowledge, skills and abilities as well as geographic location.…

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