These case studies describe project patterns and my role without exposing confidential client assets, employer-owned code, private data, or internal project materials.
Problem
Traditional client deliverables were produced using static methods in
the form of written reports and slide decks that have limited capability
to deeply explore the data behind the top level findings. In order to
improve recurring client deliverables greater organization and
standardization of information was required. One-off development of
static reporting made it difficult to maintain consistency, reduce
revision cycles, and reuse components across projects.
Role
Led development of reusable dashboard components and analytic workflows
for health workforce projection and reporting projects.
Approach
Transitioning to standardized code to reproduce regularly used analysis,
interactive dashboards and public-facing analytic outputs allowed for
increased information to be provided to client users. This increased
their knowledge of the influences on the system and allowed for greater
wisdom in decision making. My team built modular R/Shiny components,
standardized data preparation steps, improved validation workflows, and
supported deployment through Posit Connect. The framework organized
recurring deliverables around common patterns while still allowing
customization for individual clients.
Tools and methods
R, Shiny, Posit Connect, SQL, Excel, reproducible reporting workflows,
data validation routines.
What it demonstrates
Client-facing analytics delivery, reusable data product design, R/Shiny
application development, workflow modernization, and communication
across technical and non-technical stakeholders.
Problem
State and national agencies, hospital, healthcare and health profession
associations needed evidence-based estimates of future workforce supply
and demand to support policy, education, advocacy, and strategic
planning.
Role
Managed a team of economists and assisted in producing projection
modeling, analytic design, data processing, report development,
stakeholder communication, and final public deliverables.
Approach
Integrated licensing, education, demographic, survey, and utilization
data into reproducible workflows. Built projections, validated outputs,
translated results for non-technical audiences, and authored
publication-ready reports and presentations.
Tools and methods
R, SQL, Excel, survey data, administrative data, geospatial analysis,
projection modeling, reproducible reporting.
What it demonstrates
End-to-end analytic delivery, data integration, public-sector
stakeholder communication, model interpretation, and production of
decision-support outputs.
Problem
Organizations struggle with retaining institutional memory when skilled
technically capable staff move on to other opportunities.Analytic teams
often inherit fragmented files, repeated manual processes, and expensive
or overly complex data infrastructure proposals.
Role
Evaluated more practical approaches to storing, querying, validating,
and reusing recurring analytic datasets.
Approach
Developed proof-of-concept workflows using lightweight, reproducible,
analyst-friendly tools. Recommended approaches that balanced
performance, cost, maintainability, and team skill level.
Tools and methods
DuckDB, object-storage-oriented workflows, R, SQL, dataset profiling,
validation checks, documentation, reproducible pipelines.
What it demonstrates
Pragmatic data engineering judgment, architecture communication,
cost-aware technical decision-making, and ability to bridge analyst
workflows with more robust data platform practices.
Problem
Workforce data collection programs needed more complete, timely, and
policy-relevant data to support recurring reporting and strategic
planning.
Role
Led survey design, data collection strategy, data linkage, analysis, and
reporting for health workforce supply and demand studies.
Approach
Improved survey instruments, aligned data collection with licensing and
renewal processes, linked survey and administrative datasets where
appropriate, and converted recurring analyses into more repeatable
workflows.
Tools and methods
Survey design, R, SQL, administrative data, workforce licensing data,
data linkage, reporting automation.
What it demonstrates
Operational analytics, data governance awareness, public-sector
modernization, and ability to design data systems around real-world
institutional constraints.
Problem
Public reports and static tables with topm level findings were not
always sufficient for stakeholders who needed to explore workforce
patterns by geography, occupation, specialty, or demographic group.
Role
Designed and built public-facing R/Shiny and R Markdown products that
made workforce data easier to explore and communicate.
Approach
Created dashboards and reproducible reports using public or publishable
data, with emphasis on clear communication, accessible charting, and
stakeholder interpretation.
Tools and methods
R, Shiny, flexdashboard, R Markdown, ggplot2, survey data, public
reporting.
What it demonstrates
R-based data product development, public communication, and practical
experience with the kinds of analytic workflows supported by the Posit
ecosystem.