Senior AI Data Product Leader

Baylor Scott & White Health; Pierre (SD); On-site; USD 140,000 - 190,000; Full time

Job summary

Baylor Scott & White Health seeks a Senior Data Product Manager to ensure AI-ready data domains are reliable, governable, and scalable across enterprise workflows. You will own data product strategy, roadmap, and quality, working with AI product, engineering, and analytics teams.

The role emphasizes translating use cases into concrete data requirements, managing data contracts, and ensuring timely data access for AI delivery with strong cross-functional collaboration across data, governance, and

Qualifications

• Bachelor’s degree in Data Science, Information Systems, Computer Science, Engineering, Business, Healthcare Administration, Analytics, or related field.
• Master’s degree preferred.

Responsibilities

• Define product vision, roadmap, backlog, and success metrics for assigned AI-ready data products and domains.
• Translate AI use-case needs into clear data product requirements, including data elements, source systems, and quality standards.
• Prioritize data work based on AI value, urgency, and risk; create roadmaps to support current and future AI-enabled products.
• Partner with AI Product Managers, engineering, data teams, and stakeholders to identify data required to power AI use cases.
• Establish data contracts, access patterns, and governance to ensure data readiness for AI workflows.

Skills

Data product management

Cross-functional collaboration

Data governance

AI/ML readiness

Education

Bachelor's degree in data science / related field

Master's degree preferred

Tools

APIs

Data catalogs

Semantic layers

Data pipelines

Job description

Baylor Scott & White Health seeks a Senior Data Product Manager to ensure AI-ready data domains are reliable, governable, and scalable across enterprise workflows. You will own data product strategy, roadmap, and quality, working with AI product, engineering, and analytics teams.

The role emphasizes translating use cases into concrete data requirements, managing data contracts, and ensuring timely data access for AI delivery with strong cross-functional collaboration across data, governance, and