PUBLIC HEALTH · DATA SCIENCE · RESEARCH
Public health data scientist and researcher. I use data science, GIS, and research engineering to study health needs and community conditions. My work spans local dashboards, regional public health monitoring, Northeast public-health career tools, water access planning, and biomedical research.
SELECTED WORK
Live public-health products, translational research, cybersecurity evidence tooling, and community health work.
COMMUNITY HEALTH / MUNICIPAL GIS
A community dashboard for Plymouth, Massachusetts, bringing together maps, public health data, and infrastructure information. Source references help readers explore local conditions and inform research and planning.
REGIONAL PUBLIC HEALTH / FEMA REGIONS
A regional public health dashboard for the United States, organized by FEMA region. Health indicators appear alongside source references, reporting dates, and coverage information so readers can assess the available data.
PUBLIC HEALTH CAREERS / NORTHEAST
A localized job-hunt board built for public-health workers across the Northeast. JobHUD brings regional openings into one focused search surface and helps users compare roles through location, compensation, benefits, commute, and fit-oriented decision support.
BIOMEDICAL / TRANSLATIONAL
Research methods for clinical and biomedical data, including signal analysis and CAR-T eligibility questions. Documented workflows make analytical choices, assumptions, and findings easier to review and reproduce.
CYBERSECURITY / INCIDENT EVIDENCE
A terminal-style cybersecurity incident wire focused on failures, breaches, outages, vulnerabilities, and operational breakdowns. The interface emphasizes source context, evidence state, and concise incident review.
WATER / SANITATION / HYGIENE
A community water access and safety plan for McDowell County, West Virginia, with a focus on older adults. GIS analysis brings water systems, service areas, and environmental conditions into the planning process.
METHOD
Define the research question, understand its context, and assess what the available data can answer.
Record where the data comes from, what it covers, and the assumptions that shape the analysis.
Document the workflow and test the methods so others can revisit the analysis and check the results.
Share findings with their limitations and use independent review to guide the next research step.
ABOUT
Paul Skeffington, MS, MPH, works at the intersection of public health, data science, GIS, biomedical research, and responsible AI. My approach is to understand the question, examine the evidence, make the analysis reproducible, and state the limits clearly.
Across community health, biomedical research, and applied technology, I value reproducible methods and collaboration. Responsible use of AI is part of that approach, with interpretation and review kept in human hands.
CONTACT