Lead Technology Product Manager, Clinical Decision Support Adoption & EngagementAnalytics
$128,900–$226,050 year
On-siteDraper, Utah, United States
Job Summary
Define and maintain adoption, engagement, funnel, and usage metrics for clinical decision support products. Query product usage data to analyze clicks, actions, user journeys, drop-offs, cohorts, and segments. Build dashboards and recurring views that help product teams monitor performance and user behavior. Partner with Product, Engineering, Design, Analytics, Commercial, and customer-facing teams to translate analysis into clear recommendations for roadmap priorities and UX improvements. Help improve instrumentation and metric definitions so teams can rely on consistent, high-quality product data. This role requires 5+ years of experience in product analytics and strong SQL skills.
Required Qualifications
- 5+ years of experience in product analytics, data analytics, business analytics, product operations, or a related role
- Strong ability to write queries independently using SQL or comparable data-querying tools
- Experience analyzing adoption, engagement, funnel metrics, click behavior, cohorts, segments, and usage patterns and generating insights that contribute to the product development strategy
- Comfort working with event-level product telemetry, data models, and imperfect instrumentation
- Ability to turn ambiguous product questions into structured analyses and actionable insights
- Experience building dashboards, recurring reports, or self-serve product analytics views
- Strong communication skills and ability to explain data clearly to non-technical stakeholders
- Experience partnering closely with Product, Engineering, Design, Analytics, Commercial, or Customer Success teams
- Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process
Desired Qualifications
- Experience with healthcare, clinical workflow, enterprise SaaS, AI-enabled products, search, content products, or decision-support tools
- Familiarity with experimentation, A/B testing, product telemetry, event instrumentation, or customer journey analytics
- Experience with modern data platforms and business intelligence tools
- Experience analyzing qualitative and quantitative feedback together
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