Senior Technical Product Manager (Patient Engagement Experimentation)
New
Fully remote work flexibility within the United States.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of product management experience; 5+ years of hands-on experience managing A/B testing or experimentation programs at scale.
- Required Skills
- SQLProduct ManagementA/B testing
Requirements
- 8+ years of product management experience in SaaS, healthcare technology, or technology-enabled services.
- 5+ years of hands-on experience managing A/B testing or experimentation programs at scale.
- Strong expertise in multi-channel customer or patient engagement optimization.
- Experience working with or optimizing conversational or agentic AI systems, including prompt tuning or workflow refinement.
- Strong analytical skills with experience in experimental design, statistical interpretation, and data-driven decision-making.
- Familiarity with analytics and experimentation tools such as Amplitude, Mixpanel, Optimizely, or Braze.
- Knowledge of SQL and understanding of healthcare or clinical data structures is a plus.
- Experience working in Agile environments and across cross-functional product, engineering, and analytics teams.
- Strong communication skills with the ability to translate complex technical and analytical concepts into clear business insights.
- Experience in healthcare or patient engagement products is highly desirable.
Responsibilities
- Own and evolve the end-to-end experimentation and test-and-learn infrastructure for patient engagement and outreach programs.
- Design, prioritize, and execute high-volume A/B tests across multi-channel outreach systems including SMS, voice, email, and mail.
- Partner with product, engineering, and analytics teams to define hypotheses, success metrics, and measurable outcomes for experimentation initiatives.
- Analyze experiment results using statistical rigor and translate findings into actionable product and workflow improvements.
- Optimize agentic AI-driven outreach systems through continuous testing, iteration, and performance tuning.
- Develop product requirements and user stories with clear business rationale, success criteria, and data-driven validation methods.
- Establish feedback loops with QA and operational teams to ensure reliability and scalability of AI-powered engagement solutions.
- Collaborate with stakeholders to define roadmaps that balance innovation, risk, and measurable impact on patient outcomes.
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