Software Engineering + Statistical Analyses = Data Sciences

Software Engineer and Data Manager of the EAS Familial Hypercholesterolemia(FH) Study Collaboration(SC), a global registry of patient with FH. My role consists in programming data collection webapps(angular, html,CSS, java REST, javascript) as well as backend data harmonisation functions (java, talend). I interact with national lead investigators in order to integrate their requirements and suggestions within the application. Database systems used are NoSQL(MongoDB) & SQL(MySQL). I oversee the security of both data and systems, in transit or at rest. I implement statistical visualisation and reporting tools (R, R shiny, Plotly) that are accessible via the platform.

Previously, I was the Database manager/developer of the Continuous Update Project.
My main duty consisted in coding SQL queries and designing databases in order to answer epidemiologist`s demands. In complement, I programmed the Java 8 application that allows epidemiologists to analyse and manipulate the data.
I integrated R (Rserve) in the java application so that parts of the data analysis process could be done directly in the application (dose response, high vs low forest plot).
A module developed by me let user generate large datasets(csv, excel) and large reports (rtf, word) directly from the database and via the application.

Over 4 years’ experience as Microsoft Office developer. Designing VBA macros and user defined function in Excel, Word and Access. My work facilitated the administrative tasks of approximately 5000 final users.

As part of my end studies dissertation(Bsc Computer Sciences) I realized a pain management system designed for care facilities. This windows store app allows doctors to evaluate and monitor patient’s pains. The graphs integrated in this system facilitate the correlation between patients pains localization and prescriptions.

In 2009 I analyzed the Pharmacy mainframe's database of the Citadelle's Hospital in Liege.

Work Terms

Work in the evenings, weekends. In the days when workload permit it.