Senior Data Analyst, Clinical Monitoring & Analysis

Luna Health•San Diego, CA

7h•Hybrid

About The Position

Luna Health is seeking a Senior Clinical Data Analyst to own clinical trial monitoring, analysis, and reporting. This role is crucial for monitoring trial data in real time, ensuring data quality, and producing analyses and reports for clinical, regulatory, and leadership stakeholders. The analyst will work with existing clinical reporting pipelines and dashboards (SQL, Python, TypeScript, Terraform) and further develop them. The ideal candidate has solid clinical data experience, statistical depth, is comfortable in a regulated environment, and can communicate findings clearly to non-technical audiences. As the company scales, this role is expected to expand into manufacturing, quality, and business analytics.

Requirements

5+ years in data analysis, clinical analytics, biostatistics support, or a closely related role in medical devices, pharma, or clinical research.
Solid working knowledge of clinical trial methodology, endpoint definitions, protocol adherence, safety monitoring, database lock, and Good Clinical Practice expectations.
Demonstrated experience with clinical trial datasets, including EDC outputs and device data.
Strong SQL, including joins, aggregations, window functions, and data modeling concepts; hands-on experience with BigQuery or a comparable cloud warehouse.
Working proficiency in Python (or R) for analysis, visualization, and reporting.
Experience building and maintaining dashboards that other people depend on, and the judgment to decide what belongs on them.
A track record of owning analytical workstreams end to end under competing deadlines, including the willingness to sequence work and negotiate scope with stakeholders.
Ability to communicate analytical findings clearly, in writing and in presentation, to technical and non-technical audiences.
Attention to detail, a strong instinct for data quality, and the initiative to trace things that don't look right.
Comfort in a regulated environment, with rigid documentation and traceability requirements.
Must live within a reasonable commuting distance to San Diego office for onsite/hybrid work (3+ days/week).
Authorized to work for any employer in the U.S.

Nice To Haves

Experience with diabetes, CGM, or automated insulin delivery data.
Experience contributing to FDA submissions or regulatory-facing clinical reports.
Familiarity with CDISC standards (SDTM/ADaM) or HEOR modeling.
Experience with EDC platforms, like Castor CDMS.
Interest in growing into manufacturing, quality, or commercial analytics as we approach approval.

Responsibilities

Produce recurring and ad hoc analyses of trial data, including glycemic outcomes, device performance, and safety summaries.
Write clear, accurate reports for clinical, regulatory, and leadership audiences, and contribute analytical content to regulatory submissions and publications.
Support statistical analysis plan execution.
Execute health economic outcomes research (HEOR) analyses demonstrating device value to payers.
Own and extend the clinical monitoring dashboard, including glycemic outcomes, device performance, safety signals, and data completeness.
Develop clinical monitoring tools for different user tiers (internal clinical/regulatory, external CRO, external trial Site PIs or coordinators).
Own day-to-day monitoring of clinical trial data across active studies, including those leading to FDA submission.
Define checks to identify problems early, including anomalies, missing data, and out-of-range values, and escalate them.
Write and own the SQL that turns warehoused clinical data into analysis-ready datasets.
Partner with the senior data engineer on data pipeline versus analysis layer responsibilities.
Combine modern AI tools and software development best practices to build and maintain data products and tools.
Maintain a visible queue of analytics requests, assess priority, commit to dates, and identify recurring needs for reporting or dashboarding.
Maintain clear documentation of analytical methods, dataset definitions, and reporting standards.