product
Posted Apr 1Senior Product Manager - Data & AI
at Why Hiring
Remote
Responsibilities
- Product Analytics & Experimentation Execution: Implement the product analytics framework within the Integration, Adjudication and Core Data systems experiences; own tagging and data collection requirements; lead/administer A/B testing experiments, measurements and readouts; supporting the ROI model that guides investment decisions.
- Data Quality Execution: Drive prioritization, triage, and remediation workflows for data quality issues, aligned with our enterprise-level Data Quality governance standards.
- Collaborate Across the Organization – Partner with teams to understand and deliver valuable solutions.
- Grow With Us – As SmithRx scales, so will the scope and product leadership opportunities.
Requirements
- As a Senior Product Manager – Data & AI at SmithRx, you will lead the product strategy and execution for the core platform capabilities that leverage data, analytics, machine learning, and Generative AI to power automation, intelligence, and faster decision-making across our ecosystem.
- This includes developing a deep understanding of product and usage analytics to inform data driven decisioning.
- experience in health-tech, Pharmacy
- Integrations, Adjudication & Core Data Systems Intelligence: Lead data and reporting foundations / readiness, and AI-based solutions, partnering closely with the Platform Integrations & Adjudications PM team.
- AI / ML: Partner with the PM team to drive the identification, discovery, delivery and testing of new AI-based solutions within the Integrations, Adjudication & Core Data Systems Intelligence Platform product area.
- Salesforce Data Modeling & Sync: Own product requirements, data modeling, field mapping, and integration workflows across Platform <> Salesforce <> EDW to ensure scalable and accurate data availability.
- Experience in health-tech, pharmacy benefits, or healthcare data environments strongly preferred.
- Proven success launching products that leverage data science, ML, or advanced reporting and analytics.
- experience collaborating closely with engineers and data analysts. •
- Experience with complex systems, integrations, and healthcare datasets.Experience navigating complex, high-dependency technical ecosystems with multiple intersecting data domains is highly preferred.