Senior Scientist, Real-World Evidence and Outcomes

About Circadia Health

Circadia Health is a growth-stage healthcare AI company on a mission to prevent avoidable hospitalizations and transform senior-care operations. Our Circadia Intelligence Platform combines:

• Contactless sensing that monitors respiration and motion with medical-grade accuracy

• Native predictive models that detect 85% of preventable adverse events several days in advance

• Enterprise integrations that operationalize predictions directly inside EHR, care-coordination, billing, and compliance workflows

Today, our technology touches 40,000+ post-acute patients daily across skilled-nursing, home-health, and home-care networks. We are backed by leading healthcare and AI investors and headquartered in El Segundo, CA.

You will design and run the studies that establish what Circadia's platform does for patients and for cost. That means owning studies end to end: framing the question, choosing the design and comparators, running the analysis, and publishing.

Metrics you will work on include hospital readmission rates, fall rates, time to clinical intervention, emergency department and inpatient utilization, length of stay, total cost of care, and clinician productivity, such as documentation time saved by our AI scribe and charting tools.

This is our first dedicated outcomes research hire, so the scope is wide. You will own both the clinical evidence and the health economics: the peer-reviewed publications and the ROI and cost-avoidance analyses that payers, health systems, and operators ask for. You will also set the standard for how Circadia makes and substantiates claims.

You will work with the Chief Scientist, the analytics team, and clinical teams at customer facilities. Our data comes from live operations, not research protocols. It is large, real, and messy. The job is to design the strongest study that data permits, ship it, and move to the next one.

Study design and governance

Scope studies of the deployed platform: define the question, cohort, observation period, and endpoints from operational data

Choose and defend designs where randomization is not available: retrospective observational, matched cohort, difference-in-differences, interrupted time series, index-event designs

Build comparison groups, baselines, and risk-adjustment approaches that hold up under external scrutiny

Write prespecified analysis plans and decide up front what a study will and will not claim

Own IRB submission and human-subjects determination, and conflict-of-interest and AI-assistance disclosure

Shape how future deployments collect data so they are publishable by design

Analysis

Analyze Medicare claims, EHR, platform, and customer operational data

Apply matching and causal inference methods: propensity score and Mahalanobis matching, coarsened exact matching, mixed-effects models for facility-clustered data

Reason about confounding, selection bias, immortal time bias, and balance diagnostics, and argue why a cohort or comparator is defensible

Translate how Circadia operates and bills into claims-detectable logic (NPIs, place of service, RPM/RTM CPT codes, type-of-bill logic, Part A/B interaction, dual eligibility, benefit exhaustion, MDS)

Define how Circadia calculates and reports ROI and cost avoidance, and run subgroup analysis to identify where the platform delivers the strongest outcomes

Publication and dissemination

Draft and publish manuscripts in journals such as JAMDA and JAMIA, and manage peer review and revision

Produce conference abstracts, white papers, and commercial evidence from the same analysis, without letting claims drift between versions

Set the guardrails on what Circadia can and cannot claim from its evidence

Present findings to clinical, payer, and executive audiences, and support customer and partner conversations

Industry research experience is required. This role is not a fit for candidates whose experience is entirely academic

MSc or PhD in epidemiology, health services research, biostatistics, health economics, public health, or a related quantitative field

5+ years producing real-world evidence, outcomes research, or health economics work in a company, consultancy, payer, or provider setting

Experience with health economics and outcomes research: cost, utilization, ROI, or cost-avoidance analysis alongside clinical endpoints

Ability to translate technical findings into clear narratives for executives, customers, and payers

Track record of peer-reviewed publication, ideally in a clinical specialty or informatics journal

Command of observational and quasi-experimental study design, and clear thinking about its limits

Proficiency with R or Python and SQL, and comfort with large, messy healthcare datasets

Clear scientific writing, and experience carrying a manuscript through peer review

Experience with Medicare, Medicare Advantage, skilled nursing, or senior care populations

Working knowledge of Medicare claims structure and CMS post-acute quality measures (SNFRM, PPR)

Experience in remote patient monitoring, medical devices, or digital health

Experience evaluating AI or machine learning models in a clinical workflow

Experience measuring clinician workload, documentation burden, or workflow efficiency, including clinical informatics evaluation

Experience in a startup

Familiarity with IRB pathways and reporting standards such as SQUIRE 2.0

Experience working with actuarial firms or third-party claims datasets

Understanding of value-based care economics and healthcare reimbursement

Based in our El Segundo office, five days per week. Occasional travel to skilled nursing facilities, hospitals, and conferences in California and beyond.

Reasonable accommodations will be provided in accordance with applicable federal and California law.