$ ls -1Gp projects/ Duolingo Analysis/
Anime Recommender System/
Twitter Scraper (21 stars)/
Pokémon Neural Network/
Markov-Chaining Twitter Bot/
Natural Language Processing with Genomics/
Twitter DNA Bot/
Is It Filler?/

$ ls languages/ Python    SQL            C++          Scala
R         Shell (BASH)   Java         LaTeX

$ cd experience/ && ls -RpG internships/     research/

./internships:
West Bend Mutual Insurance/      Arity (an AllState company)/      Capital One/

./internships/West Bend Mutual Insurance:
Software Engineer.intern          Summer2017

./internships/Arity (an AllState company):
Data Analyst Engineer.intern      Summer2018

./internships/Capital One:
Data Engineer.intern              Summer2019

./internships/Amazon:
Software Engineer.intern          Summer2020

./research:
Engelman.lab     2015-2017       Alzheimer's Disease      Machine Learning
Payseur.lab      2017            Mice Genetics            Automated Image Processing
Ong.lab          Summer2017      Cancer                   Data Visualization
McMahon.lab      2018-2019       Metagenomics             Big Data
Schwartz.lab     2020            Cancer Modeling          Linear Programming

$ perl -pe "s/\t/: /g" about_me.tsv Home state: Wisconsin
Age: 24
Cats: 3
Hobbies: Lifting, bouldering, unnecessary automation, Overwatch

$ history In 2015 I began attending the University of Wisconsin, the shared alma mater of both my parents. In the first month, I became involved in a computational epidemiology lab that focused on Alzheimer's research. Much of my work revolved around the application of machine learning (ML) methods to human data. I worked with Random Forests to characterize gene-gene and gene-environment interactions with the goal of identifying predictors for Alzheimer's. Next, I worked on a project where I reduced the dimensionality of metabolomic data before the application of clustering methods and other analyses by the lab. Under the direction of Dr. Engleman, I presented my work with metabolomics and RandomForests at the 2016 Undergraduate Research Symposium.

After my mentor entered her doctoral year, I transitioned to a genetics lab where I spent a semester designing and implementing a program to process microscope slides of mice chromosomes. I chose MATLAB for its image analysis libraries. The program was able to deconstruct the images and distinguish overlapping chromosomes, with light supervision.

I worked for Summer 2017 as a Software Developer at West Bend Mutual Insurance, where I authored programs in C#, R, and VBA to manipulate excel spreadsheets and compose SQL queries to build a MySQL Database. It was here that I also gained a lot of experience in Javascript, CSS/HTML, and Angular.js, working with the Senior Business Analyst to tailor internal webpages for company use.During my free time I taught myself Python and Scala, gamed, and rock climbed.

Taking a break from research for a semester to focus on my grades, I discovered a passion for competitive programming and hackathons, traveling as far as Massachusetts after getting admitted to HackMIT. It was during this semester that I took Operating Systems and Artificial Intelligence and began transitioning from a prospective career in bioinformatics software to Data Science. I sought out relevant research for the follow semester and was offered a long-term position in a bacteriology research lab, where I use Python, R, and extensive shell scripting to maintain a data pipeline for hundreds of gigabytes of metagenomic data. For summer 2018 I worked as a Data Analyst Engineering Intern for Arity, the predictive analytics brainchild of AllState. I built from scratch a Scala pipeline that would ingest millions of records of trip data on a daily basis and generate a report to monitor the incoming batch of data. The report was generated using Rmarkdown and the Tidyverse package, and the overall pipeline was wrapped in BASH.

In the middle of my junior year, I founded UW Madison's Data Science Club, which has grown to over 300 members since its inception. I led it until my graduation, organizing workshops, contacting local companies and organizations to give lectures and present special topics, and introducing undergraduates to researchers who needed help doing analytics work.

After graduating in 2019, I completed an Chaos Engineering internship with Capital One before proceeding to my graduate program at Carnegie Mellon University to study Computational Biology. For my 2020 summer internship, I was accepted into Amazon's Graduate Intern program and worked as a Software Engineer in their research org.

As I write this now, I'm completing my third semester as an MS student. I'm taking courses such as Cloud Computing, Computational Data Science, and Neural Computation, and applying to PhD programs as well as full time Data Science jobs. Thanks for reading!

You can see some of my projects (including Hackathon projects) on my personal GitHub.