Ivan Berlin
Programmer && Musician
Ivan Berlin is a third-year Computer Science and Cognitive Psychology major at Northeastern University who has a passion for programming, composing music, playing and analyzing videogames, and cats.
He is currently exploring how to interweave his wide array of interests by studying - and applying himself to - new programming domains, music genres, music production programs, and game-related software. His witty sense of humor is equally loved and hated by his friends and family.
Education
Northeastern University - Boston, MA
Bachelor of Science in CS + Cognitive Psychology, 2021 - 2025
GPA: 3.975 / 4.0
Consistent Khoury College Dean's List Student
MAST @ FIU - NMB, FL
High School Diploma, 2017 - 2021
Unweighted GPA: 4.0 / 4.0
Graduated Magna Cum Laude
Experience
Software Engineer Intern
Instawork
January 2023 - June 2023
Throughout my internship at Instawork, I contributed value to both my coworkers and to the company's userbase across several programming and business-side domains. I simplified an Operations workflow to improve their productivity through a new feature. Similarly, I created a dynamic dashboard for a manager, enabling her to have a quicker overview of the information she needed as well as view metrics that she could not access before. Additionally, I documented my code thoroughly to assist my fellow programmers who might revisit it and I created extensive unit tests and manually tested user-facing flows in mobile simulators to better assist other programmers and QA with my new changes or fixes. On the user side, I fixed both backend and frontend-related bugs that had negatively impacted the user experience, and I implemented new features to simplify user flows.
My work culminated in creating a v1 for a new, large, end-to-end feature. I incorporated the best patterns and practices I observed throughout my time at Instawork to cleanly integrate the new feature into the existing backend framework and front-end flow. I wrote a TAD (technical approach document) to summarize my work and elaborate on how future extensions could most easily be implemented.