Lead Decision Scientist - AI Product

CVS Health•Work At Home-Illinois, IL

1d•$130,295 - $260,590

About The Position

CVS Health is seeking a Lead Decision Scientist - AI Product to lead the product strategy, roadmap, and execution for a multi-agent AI decision intelligence platform. This role will serve as the bridge between business stakeholders, data science, engineering, and operations teams to deliver scalable AI-powered solutions that improve decision-making, operational efficiency, and business outcomes across Specialty Operations. The Lead Decision Scientist - AI Product will be responsible for defining platform capabilities, prioritizing investments, and driving the development of agentic AI workflows, predictive analytics solutions, and decision intelligence products. This individual will translate complex business challenges into product requirements, manage cross-functional delivery teams, and ensure the platform delivers measurable value to operational users and business leaders. The ideal candidate combines strong product management expertise with technical depth in AI, data science, and enterprise platforms. They are comfortable working with executive stakeholders, understanding operational workflows, and driving innovation in a rapidly evolving AI landscape.

Requirements

7+ years of product management experience, including ownership of technical products, data platforms, analytics products, or AI/ML solutions
Experience defining product strategy, roadmaps, and requirements for enterprise-scale technology platforms
Strong understanding of AI, machine learning, and decision support systems
Experience partnering with engineering, data science, and business teams to deliver complex technology solutions
Ability to translate business problems into technical requirements, user stories, and product specifications
Experience managing cross-functional stakeholders and influencing decisions across multiple organizational levels
Strong analytical and problem-solving skills with the ability to leverage data to prioritize product investments
Experience leading Agile product development processes and working closely with software engineering teams
Excellent communication and presentation skills, including experience presenting to senior leadership
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Business, or a related field required

Nice To Haves

Experience developing or managing AI agent, multi-agent, or generative AI platforms
Experience with decision intelligence, operational analytics, workflow automation, or intelligent decision support systems
Healthcare, pharmacy, specialty pharmacy, or healthcare operations experience
Familiarity with modern AI ecosystems, including large language models (LLMs), agent orchestration frameworks, vector databases, retrieval-augmented generation (RAG), and model evaluation methodologies
Experience managing platform products that support multiple business use cases and stakeholder groups
Consulting experience or experience leading strategic technology transformations
Familiarity with cloud-native architectures and platforms such as AWS, Azure, or GCP
Experience defining KPIs, adoption metrics, and value realization frameworks
Knowledge of responsible AI, model governance, and AI risk management principles
Master’s degree in Business Administration (MBA), Computer Science, Engineering, Data Science, or a related discipline preferred

Responsibilities

Lead the product strategy, roadmap, and execution for a multi-agent AI decision intelligence platform.
Serve as the bridge between business stakeholders, data science, engineering, and operations teams.
Deliver scalable AI-powered solutions that improve decision-making, operational efficiency, and business outcomes across Specialty Operations.
Define platform capabilities, prioritize investments, and drive the development of agentic AI workflows, predictive analytics solutions, and decision intelligence products.
Translate complex business challenges into product requirements.
Manage cross-functional delivery teams.
Ensure the platform delivers measurable value to operational users and business leaders.
Work with executive stakeholders, understand operational workflows, and drive innovation in a rapidly evolving AI landscape.