Job Summary
The Database Analyst Senior will evaluate, design, and maintain database systems to support a high-volume, methodologically rigorous research portfolio within the Department of Emergency Medicine. This role focuses on structuring, integrating, and managing complex clinical and research data sources?including emergency medical services (EMS), electronic health records (EHR), and clinical registries?to support clinical trials, observational studies, and outcomes research in acute neurologic emergencies.

The individual will work with minimal supervision and exercise independent judgment in the design and implementation of database solutions. This position partners closely with investigators, analysts, and clinical teams to ensure data integrity, accessibility, and alignment with research and operational objectives. Consistent with U-M senior-level classifications, assignments are broad in scope and require originality, ingenuity, and independent decision-making.

Responsibilities*
Database Design, Analysis & Systems Development (40%)

Evaluate and design database structures to support research and operational data needs
Develop data models, schemas, and architecture for multi-source healthcare datasets
Maintain comprehensive documentation including data dictionaries, data flow diagrams, and system specifications
Lead and support statistical design for database analyses, and pragmatic clinical trials in emergency and neurovascular care
Develop analytic plans addressing time-critical care processes (e.g., scene time, transport decisions, door-to-treatment intervals)
Data Infrastructure & Management (20%)

Design and maintain processes for data extraction, transformation, and storage across HER, EMS datasets, and clinical registries
Build and maintain data pipelines for large, complex datasets
Perform data cleaning, validation, and reconciliation across multiple sources
Ensure data quality, integrity, and compliance with institutional and regulatory standards
Conduct ongoing validation of data infrastructure to ensure accuracy and usability
Data Integration & Analytics Support (20%)

Perform deterministic or probabilistic linkage across prehospital and hospital datasets
Prepare analysis-ready datasets in collaboration with biostatisticians and investigators
Translate clinical workflows and study designs into structured data elements
Support development of datasets for clinical trials, registry studies, and health services research Perform sample size and power calculations for grants and manuscripts
Provide methodologic input for NIH, AHA, DoD, and foundation proposals
Programming, Reproducibility & Visualization (10%)

Primary programming in Stata or R (required); SAS experience strongly preferred
Proficiency in ArcGIS
Develop reproducible workflows using R Markdown/Quarto and version control (Git)
Create publication-ready tables and figures (e.g., forest plots, flow diagrams, time-to-event curves)
Support transparent and reproducible analytic pipelines aligned with journal and funder expectations (developing Statistical Analysis Plans to be included in publications)
Present data findings and support interpretation for multidisciplinary teams
Collaboration, Communication & Mentorship (10%)

Collaborate with clinicians, researchers, and operational leaders across departments
Serve as a technical resource for database design and data management best practices
Mentor junior analysts and research staff in data management and workflow development
Contribute to grant submissions, manuscripts, and regulatory documentation
Prepare statistical methods/results sections and respond to reviewer comments
Clearly communicate findings to clinicians, trainees, and multidisciplinary collaborators
Required Qualifications*
Master's degree or higher in biostatistics, computer science, data science, health informatics, or a related field
Experience in database design, data management, or healthcare analytics
Experience working with large, complex datasets (e.g., EHR, registries, administrative data)
Demonstrated ability to independently design and implement database solutions
Excellent organizational, analytical, and communication skills
Desired Qualifications*
Experience with national registry datasets like American Heart Association Get-With-The-Guidelines-Stroke
Experience with EMS, stroke, trauma, or neurocritical care datasets
Familiarity with clinical research data structures and workflows
Experience with programming languages such as R, Python, SAS, or Stata
Experience with dashboarding and visualization tools (Tableau, Power BI)
Prior experience supporting NIH, AHA, or other federally funded research
Statistical Methods (Expected Proficiency)
Multivariable regression (logistic, linear, Poisson/negative binomial)
AUC analysis / ROC curves for diagnostic studies
Time-to-event and survival analyses (including competing risks)
Hierarchical and mixed-effects models (patients nested within EMS agencies, hospitals, or regions)