AI-Driven Data Product Leader

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

Benefits offered by this job

Immediate eligibility for health and_w

401(k) savings plan with dollar-for-d​

Tuition Reimbursement

PTO accrual beginning Day 1

Job summary

Baylor Scott & White Health seeks a Senior Data Product Manager to lead data domains powering AI initiatives, ensuring data quality, governance, availability, and lifecycle management for enterprise workflows. The role partners with AI Product, Engineering, Knowledge/Ontology, Analytics, Security, and Operations to translate use‑case needs into concrete data product requirements.

This role emphasizes data readiness, contracts, and collaboration across clinical, operational, and financial

Qualifications

• Bachelor’s degree required in a related field.
• Master’s degree preferred for advanced analytics leadership.
• 10–15 years of experience in data product management, governance, analytics, or related tech roles.
• 5–10+ years owning data products, data domains, or analytics platforms.

Responsibilities

• Own data domain strategy, roadmaps, backlog, and success metrics for AI-ready data products.
• Translate AI use‑case needs into data requirements, contracts, and quality standards.
• Prioritize data work based on AI value, urgency, risks, and feasibility.
• Partner with AI Product, Engineering, Analytics, and Governance teams to enable AI use cases.
• Define data contracts, access patterns, and readiness criteria for data products.

Skills

Data product management

Data governance

Data quality management

AI readiness

Cross-functional collaboration

Stakeholder alignment

Analytical skills

Education

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

Master’s degree preferred

Job description

Baylor Scott & White Health seeks a Senior Data Product Manager to lead data domains powering AI initiatives, ensuring data quality, governance, availability, and lifecycle management for enterprise workflows. The role partners with AI Product, Engineering, Knowledge/Ontology, Analytics, Security, and Operations to translate use‑case needs into concrete data product requirements.

This role emphasizes data readiness, contracts, and collaboration across clinical, operational, and financial