About the job
As a Clinical Specialist, you will work as part of the cross-functional team building personalized AI-powered health and wellness products to help people lead healthier and more active lives. You will use your clinical expertise to guide research and product development for the Fitbit and Pixel portfolio of trackers, smartwatches, and subscription experiences. You will help ensure our approach is grounded in scientific and clinical accuracy and creates measurable value for people who want to use our products to help improve their health and wellbeing.
Responsibilities
Lead clinical evaluation requests and drive the technical execution of safety workstreams with minimal guidance.
Lead the identification and design of analytical methods to measure clinical/health outcomes, including establishing "office hours" for evaluation best practices, and independently drive the execution of clinical project strategies.
Serve as the primary clinical point of contact for internal product teams carrying out evaluations, ensuring all deliverables meet Google's high-integrity standards.
Maintain competency in the evolving technical landscape to translate complex safety insights into user-focused product requirements.
Use clinical and domain expertise to provide guidance, insights, and direction on health information quality for Google’s health-focused products and platforms, helping to assess benefits to people’s health as well as potential issues related to safety, health literacy, and health equity.
Qualifications
Minimum
Clinical degree (e.g., PharmD, DNP, MD, DO, MBBS, etc.), and 3 years of clinical experience after the completion of clinical degree.
Postgraduate clinical training, as demonstrated by completion of accredited residency, fellowship, equivalent certification, or equivalent work experience.
3 years of experience leading projects with cross-functional teams.
1 year of experience with AI in a health or healthcare setting.
Preferred
Experience in implementing quantitative evaluation pipelines (e.g., SQL, Python-based statistical or epidemiological analysis) with a strong research methods background.
Experience taking a digital health product from concept to market or clinical use.