Jai Broome

Research Scientist & R programmer

Scroll down. Or, download my résumé.

a little about me

I am a Research Scientist in the Division of General Internal Medicine at the University of Washington where I lead the genetic analysis component for a diverse portfolio of Alzheimer’s Disease research projects. If you want to get in touch, please contact me however is convenient.

Previously, I was a Research Scientist in the Division of Medical Genetics, where I maintained the analysis pipeline for the Blue Lab and ran start-to-finish GWAS; at the UW Genetic Analysis Center, where I primarily harmonized phenotype data across TOPMed studies; and a Project Coordinator at the Human Nature Lab at the Yale Institute for Network Science, where I was responsible for research support. Prior to joining the Human Nature Lab, I graduated from Northwestern University with a Bachelor of Arts in economics and a GPA of 3.49.

Skills

Data analysis, visualization and tidying with R and Excel

Reproducible programming notebook tools R Markdown & knitr

Version control with Git and GitHub

Basic quering and joining with SQL

Graphic design with Adobe Photoshop and InDesign

Basic web design and familiarity with HTML/CSS

Online computing and office software, including Microsoft Office and Google Docs

Experienced writing in multiple styles, including Associated Press and Modern Language Association

Proficient in recording and editing video and audio

Public speaking and small group presentation

Projects

After discovering a software glitch that led to certain data points being systematically overwritten in a survey, I wrote a script in R to identify observations where data were lost and calculate the extent of the problem. As a result, we were able to fix the software before more data were lost, and revisit study participants for whom we had missing data.

As the person primarily responsible for keeping projects in compliance with federal and University regulations, I devised a system to track expiration dates, protocol amendments, and updates from project personnel.

odds and ends

I’m passionate about reproducible research and promoting sound research methods.

I spend a lot of time thinking about how to organize my podcast feeds.

I grew up outside a tiny town in Oregon.

Sometimes I worry if I’m pithy enough on Twitter.

sample data project

This is the code for my submissions to Kaggle’s 2016 March Machine Learning Mania competition. My approach was to summarize teams’ game-level statistics by season to predict outcomes in tournament matchups, and weight by tournament seed. My submission finished the tournament with a logloss score of 0.614.

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