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Bayesian Health

AI-powered clinical data insights platform

Clinical Quality Consultant

Regulatory & Quality (Life Sciences)Confirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • Five years of experience, with either an active registered nurse license and at least three years of acute care experience (for example, ICU, emergency, or rapid response) plus strong familiarity with sepsis and clinical deterioration, or commensurate healthcare experience and the ability to understand clinical aspects of sepsis and clinical deterioration.
  • Experience with electronic health records such as Epic or Cerner, or work in clinical informatics, clinical research, or clinical decision support.
  • Exposure to SEP-1 or sepsis bundle abstraction and quality reporting.
  • Familiarity with medical device quality standards such as QMSR or ISO 13485, or eagerness to build that knowledge.
  • Comfort reading structured clinical data exports and spreadsheets.
  • Current, unrestricted authorization to work in the United States.
  • Sound judgment and the ability to reason from vitals, labs, medications, and documentation to a defensible conclusion.
  • Clear written communication suited to clinician and clinical informatics audiences.
  • A record of completing work without close supervision in an environment where processes are still taking shape.
  • Evidence of fixing processes rather than working around them, including finding something broken, changing it, and documenting the fix.
  • Ability to learn a technical product quickly and reason about it accurately, including asking appropriate questions of engineering and data science.
  • Fluency with AI tools in daily work and the judgment to verify their output.
  • Comfort working in a ticket-driven, data-heavy environment while staying organized and accurate across concurrent cases.
  • Interest in learning medical device quality and regulatory practice, including complaint handling.

Responsibilities

  • Perform clinical case reviews on sepsis alerts by examining encounter records, establishing the clinical timeline, determining whether the alert behaved as designed, and producing an internal review with cited evidence and a recommended next action.
  • Build and apply working knowledge of how the product generates, suppresses, and delivers flags, including the electronic health record data that drives them, so conclusions withstand clinical and technical scrutiny.
  • Review AI-assisted triage and classification, including investigation and complaint classification, ticket creation, and draft acknowledgements, and correct outputs unsupported by clinical facts.
  • Write accurate responses to clinicians and clinical informatics teams following communication standards that protect patient privacy and avoid giving clinical direction.
  • Own escalations by routing issues to the accountable data science, engineering, implementation, or clinical team, providing clinical context, and driving tickets through to closure.
  • Send close-out communications and close resolved tickets.
  • Manage a concurrent caseload against response commitments by tracking status, prioritizing by clinical and client risk, and keeping the queue current without prompting.
  • Identify recurring patterns across cases, such as mapping failures, interface latency, or suppression gaps; quantify their frequency and raise them with the owning team.
  • Create and improve case review templates, evidence standards, response language, triage rules, and escalation paths, and document them so subsequent reviewers can reach consistent conclusions.
  • Support product complaint handling by documenting complaints and assembling required clinical evidence, and, once trained, contribute to disposition of possible anomalies as part of the regulated-device release process.

About the Company

Bayesian Health

AI-powered clinical data insights platform

Bayesian Health uses AI to help hospitals turn raw healthcare data into real-time, actionable insights for clinicians. Its platform continuously analyzes patient data and care workflows to support proactive, higher-quality care, especially for patient outcomes. How it works: a subscription-based platform that integrates with existing hospital systems, processes real-time data, and presents clinicians with actionable insights. It also provides ongoing updates, training, and customization to fit each provider’s needs. How it stands out: it combines rigorous scientific methods with practical AI tools, emphasizes real-time data analysis and proactive care, and offers strong integration and support typical for biotech-grade solutions. Its goal is to improve patient outcomes by enabling care teams to act on timely, data-driven insights inside hospitals.

Company size
11-50
Company stage
Late Stage VC
Total funding
$30.2M
Headquarters
New York City, New York
Founded
Not listed

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