- Provided expertise in data analysis, data visualization, research, analytical writing, and object-oriented programming.
- Used software and programming languages such as R/RStudio, RShiny, Rmarkdown, SQL, Python, Unix/Linux, and AWS Cloud Resources.
Chris Curran
About
Chris Curran has four years of experience as a data analyst and engineer with skills in software and programming languages such as R/RStudio, RShiny, Rmarkdown, SQL, Python, Unix/Linux, and AWS Cloud Resources. His expertise lies in data analysis, data visualization, research, analytical writing, and object-oriented programming. At PatientsLikeMe, Chris implemented repeatable analytic solutions and designed dashboards to reveal data insights, including inManu Jeevan Prakash teractive visualizations.
Employment
PatientsLikeMe is a for-profit patient network and real-time research platform.
- Designed and implemented repeatable analytic solutions, using a combination of R, Python, SQL, and Amazon AWS Cloud Resources.
- Worked cooperatively, designed project plans, determined scope, and executed on desired outcomes.
- Designed dashboards to reveal data insights, including interactive visualizations.
- Advised project teams on what data is available and the limits on what the available data can used for.
PatientsLikeMe is a for-profit patient network and real-time research platform.
- Performed quantitative analysis of patient generated health data, including patient reported outcome measures, survey data, and other health related data.
- Applied descriptive, comparative, and basic regression methods to answer key questions.
- Independently executed project plans and SOW’s, moving projects from inception to delivery.
- Created deliverables (e.g., PowerPoint, dashboards, written reports, etc.) to communicate project results to relevant stakeholders.
- Automated reporting systems of patient reported health data using R/RStudio and SQL (Postgres).
PatientsLikeMe is a for-profit patient network and real-time research platform.
- Performed descriptive data analysis and visualization.
- Created analysis ready data sets, using multiple data sources.
- Provided training, oversight, and support to junior research staff.
- Coded, QA tested, and fielded health related surveys to communities of patients online.
- Performed preliminary analysis of survey data.
- Performed preliminary literature reviews (i.e., PubMed, GoogleScholar, etc.) to inform survey development and analysis.
- Triaged patient feedback and concerns regarding surveys.