Product Manager

• “Applicants must be authorized to work in the U.S.”
• “We are unable to sponsor work visas.”'

Job Summary:

• Lead the development and deployment of AI/ML-driven healthcare products that enhance patient care, streamline clinical workflows, and deliver measurable ROI. Bridge the gap between technical teams and healthcare stakeholders to build ethical, scalable solutions.

Key Responsibilities

Product Strategy & Vision

• Identify high-impact AI/ML use cases (e.g., clinical decision support, operational efficiency).
• Conduct market research and stakeholder interviews (clinicians, admins) to uncover unmet needs.
• Define ROI-driven roadmaps for AI/ML investments.

Product Lifecycle Management

• Own end-to-end product development: ideation → launch → iteration.
• Write detailed requirements/user stories for AI/ML models and workflow integration.
• Prioritize backlogs and make data-driven roadmap decisions.

AI/ML & Healthcare Expertise

• Apply knowledge of AI/ML methodologies (e.g., NLP, predictive modeling) to solve healthcare challenges.
• Navigate healthcare regulations (HIPAA, interoperability), ethical AI, and data privacy.
• Evaluate model feasibility and impact (e.g., reducing clinician burnout, improving diagnostics).

Cross-Functional Collaboration

• Translate technical concepts for non-technical audiences (execs, clinicians).
• Align engineering, data science, design, and business teams.

Performance Optimization

• Design evaluation strategies (online/offline/human-in-the-loop testing).
• Track KPIs (e.g., model accuracy, adoption rates, cost savings).
• Iterate based on user feedback and performance data.

Qualifications

Required

• 5+ years in AI/ML product management (healthcare preferred).

Strong understanding of:

• AI/ML concepts (e.g., supervised/unsupervised learning, LLMs).
• Healthcare workflows (clinical, administrative) and regulations.
• Proven ability to define ROI-driven roadmaps and manage technical backlogs.
• Exceptional communication and stakeholder management skills.

Preferred

• Background in health tech, FHIR/HL7 standards, or responsible AI.
• Experience with cloud platforms (AWS/GCP/Azure) and MLOps.
• Certifications: PMP, Agile, or AI/ML (e.g., Google Cloud ML Engineer).