Resume
KALEB GETACHEW
Seattle // 571-481-0220 // kg9rv@virginia.edu // LinkedIn // HackerRank // Github
Major: Computer Science and Statistics
EDUCATION
B.S. COMPUTER SCIENCE, University of Virginia, CS GPA: 3.7 Graduated: May 2022 Core Courses: Algorithms, Statistics, Program & Data Representation, Machine Learning, Statistical ML, Ad- vanced Software Engineering, ML for Statistics, CyberSecurity, Computer Architecture, Discrete Math, Probability, Operating Systems, Computer Vision, Data Analysis, NLP, Databases
SKILLS
Programming Languages: Python, Java, Kotlin, C++, C, C#, JS, CSS, HTML, SQL, NoSQL, R, Lean, OCaml Technologies:REST, Git, Spring Boot, ReactJS, Docker, Kubernetes, Temporal, Datadog, Mockito, Maven/Gradle
PROFESSIONAL EXPERIENCE
SoFi - Invest Team Seattle, WA Software Engineer (Jul 2022 - Mar 2023)
- Collaborated with co-workers in automating git CI/CD pipelines during a 2-week company-wide Hackathon
- Contributed with Invest team in developing Options Trading platform for web and mobile applications over 6 months
- Designed and implemented a new document-saving process, improving security and stability by 15%, benefiting thousands of users
PayPal - World Ready Team Remote Software Engineering Intern (Jun 2021 - Sep 2021)
- Focused on improving overall quality effect of PayPal sites from 77% to 90%
- Engineered and documented Polish language model APIs for in-house use, adhering to PayPal standard
- Co-authored, trained, and tested multiple Natural Language Generation models within 12-weeks using Python to personalize various PayPal web-pages
PayPal - Collections Team Remote Data Science Intern (Jun 2021 - Sep 2021)
- Identified top-performing variables from collections database influencing dialing volume to customers
- Finalized project using Tableau, and JupyterNotebooks to clearly, and accurately convey findings
PROJECT EXPERIENCE
FitUVA (Feb 2021 - May 2021)
- Utilized industry services such as Heroku Cloud, Django, and Postgres
- Co-designed and co-developed a website to gamify fitness through tracking exercises, joining fitness groups, and awarding badges, achieving 95% user satisfaction
Restaurant Recommender ML4VA Presentation (Aug 2020 - Dec 2020)
- Employed models such as: Random Forests, Logistical, Decision Tree, Adaboost, and Bagging Models
- Gathered and cleaned diverse, open-source, data containing 300+ entries across Virginia
- Collaborated with 3 others to write, train and test an ensemble of classifiers to recommend restaurants based on personal inputs, achieving 90% precision and accuracy
LEADERSHIP
ColorStack - President: Assembled 10 students to establish 1st ColorStack chapter at UVA, striving to increase entrance, retention and success of Black, Latinx, and Native American college students in computing.
ORGANIZATIONS
- National Society of Black Engineers (NSBE)
- Machine Learning Club Chess Club
- CyberSecurity and Networking Club (CNS)
- Ethiopian-Eritrean Student Association (EESA)
- Data Science Club (DSAC)