Job Description​

• Define and implement the product strategy and roadmap for healthcareanalytics portfolio. 

• Align product development with market trends, customer needs, and strategic priorities.

• Influence enterprise product vision by contributing insights on competitive positioning, emerging opportunities, and customer pain points.

• Own the full product lifecycle:requirementsdefinition, design, development, testing, launch, and post-launch optimization.

• Translate business and market needs into actionable product features and analytics solutions.

• Ensure product solutions are differentiated, value-driven, and aligned with customer outcomes.

• Apply deep healthcare dataexpertise(claims, payer/provider analytics, value-based care) to enrich product offerings.

• Identifyinnovative methodologies and advanced analytics techniques to strengthen BCBSA’s solutions.

• Champion adoption of modern product practices (agile, data-driven roadmaps, customer co-design).

• Partner with Finance, Sales, and Marketing on pricing, positioning, and go-to-market strategies.

• Lead customer engagements including training, advisory sessions, ROI analysis, and industry forums.

• Build strong relationships with customers, internal stakeholders, andindustry thoughtleaders.

• Mentor product analysts and managers, fostering professional growth and building product leadership capabilities across the team.

• Guidecross-functional project teams including engineers, data scientists, designers, and architects.

• Ensure adherence to SOC 2, HIPAA, and other compliance standards across product solutions.

• Promote responsible handling of sensitive healthcare data.

Education

• Bachelor’s degree in public health, Life Sciences, Computer Science, or related field
• Master’spreferred

Experience

• 10+ years of experience in product management, with proven success owning roadmaps and delivering healthcare data products.
• Extensive hands-on experience with payer, provider, and pharmacy analytics, including claims data.
• Experience leading or supporting AI, machine learning, advanced analytics, data platform, or agentic product capabilities in a healthcare, payer, provider, or enterprise data environment.
• Experience partnering with engineering, data science, compliance, security, and business teams to evaluate product tradeoffs, manage risk, and support scalable deployment of data-driven or AI-enabled solutions.
• Experience working on a product through a 0-to-1 or early-growth phase.
• Preferred: Experience with AI-enabled analytics products, agentic AI platforms, natural language interfaces, or products that enable non-technical users to access, interpret, or act on complex data.

Knowledge, Skills and Abilities

• Strong knowledge of population health management, value-based care programs, and healthcare ecosystem trends.
• Demonstrated ability to translate complex analytics, data science, or AI-enabled capabilities into clear product requirements, user workflows, adoption strategies, and measurable customer outcomes.
• Track recordof developing innovative, data-driven solutions that drive measurable customer and business outcomes.
• Proven ability to influence executives, customers, and cross-functional teams.
• Excellent communication and presentation skills, with experiencerepresenting products in customer and industry settings.
• Familiarity with compliance frameworks (SOC 2, HIPAA) and secure product practices.
• Working knowledge of modern AI concepts, including generative AI, large language models, agents, retrieval, prompting, and responsible AI practices, with the ability to apply these concepts to product strategy and decision-making.
• Ability to assess AI-enabled product opportunities through the lens of customer value, usability, reliability, data quality, security, compliance, and measurable business impact.
• Strong ability to translate between technical teams, business leaders, product teams, and end users to ensure AI-enabled solutions are understandable, usable, and aligned to customer outcomes.
• Familiarity with enterprise data ecosystems, analytics platforms, and cloud-based data environments such as AWS, Snowflake, Databricks, or similar platforms.
• Ability to promote responsible handling of sensitive healthcare data, including awareness of AI-specific risks, data sensitivity considerations, transparency, and appropriate human review.