Manager, Data Science

Manager, Data Science

A part of Colgate-Palmolive since 1976, Hill's Pet Nutrition offers the highest-quality pet nutrition available through product lines Prescription Diet® and Science Diet®. Veterinarians worldwide recommend and feed their own pets Hill's products more than any other brand of pet food. Available in approximately 80 countries around the world, our extensive line of products includes more than 60 Prescription Diet brand pet foods and more than 50 Science Diet brand pet foods.

We believe all animals should be loved and cared for during their lifetimes. That is why we are proud our pet foods can make a difference in your pet's life. A career at Hill's Pet Nutrition or Colgate-Palmolive is an excellent opportunity if you seek a global experience, constant challenge, and development opportunities in an environment that respects work/life effectiveness.

Role

Summary:

The Manager, Data Science leads the end-to-end development, deployment, operationalization, and optimization of scalable advanced analytics, machine learning, and Generative AI solutions for the global marketing and sales organization while leveraging scalable data products. Reporting directly to the Director, Global Data Science, this role acts as a strategic analytics translator and change agent, bridging technical data science capabilities with commercial goals.

Leveraging expertise to utilize cloud infrastructure, robust MLOps practices, and quantitative modeling, the Manager drives data-informed decision-making that delivers quantified value realization, directly accelerating global sales growth and pet care innovation.

Responsibilities:

• Adopt a data product mindset to apply and utilize scalable data products within advanced analytics, defining, framing, and prioritizing complex commercial challenges into high-impact analytics roadmaps while serving as an analytics translator and advocate for data-driven decision-making to drive quantified value realization (e.g., direct P&L impact, measurable revenue uplift, and automated efficiency gains).
• Lead the end-to-end development, deployment, operationalization, and lifecycle management of predictive, machine learning, and Generative AI / Large Language Models (LLMs) to solve critical sales and marketing challenges across workflows for unstructured data, feature engineering, and automated insight generation.
• Help lay the foundation for MLOps practices, CI/CD pipelines, model monitoring, and governance frameworks to support model performance, reliability, and security as our AI/ML capabilities mature.
• Design, execute, and evaluate continuous experimentation protocols, including A/B testing and causal inference, to measure and improve commercial outcomes.
• Partner with cross-functional commercial leaders, external vendors, and IT/data engineering teams to leverage enterprise cloud data infrastructure (AWS/Azure) and ML tooling as we mature our cloud environment.
• Build and automate interactive reporting dashboards using platforms such as Tableau, Domo, or Google Data Studio to deliver actionable insights to non-technical stakeholders.
• Drive change management and user adoption strategies, partnering closely with business stakeholders to transition AI capabilities into everyday commercial operations.

Required Qualifications:

• Bachelor's Degree in Data Science, Statistics, Computer Science, Business Analytics, or a related quantitative field.
• 5+ years of experience in applied data analytics, data science, quantitative programming, or a related field.
• Hands-on proficiency with SQL and Python or R for statistical modeling and predictive analytics.
• Experience designing and executing A/B testing frameworks and applying modern Generative AI techniques, Large Language Models (LLMs), and…