This summer, I interned as a Data Scientist at AppliedX, part of Applied Materials's edtech division. I created descriptive visualizations for various business units in the company using Tableau, preprocessing data from Microsoft SQL Server using Pandas, and analyzed major causes of roles changing using logistic regression and Bayesian inference. I also developed a recommendation algorithm to connect employees with one another based on content-based filtering and document similarity using NLTK, Scikit-Learn, Pandas, Scipy, and Numpy, applied over a based of 13,000 employees. I productionized the algorithm by designing and developing a web app, and iterated on feedback from users from both within and outside the group.
I interned at CivikOwl last summer 2017 working on software development. I learned technologies like ReactJS, D3.js, and jQuery, which greatly improved my skillset as a frontend developer, followed up on my interest in civic tech, and picked up concepts of the Agile methodology, human-centered design, and product management. I added major features (both web and mobile) to a web app and also created a data visualization of users' news reading habits, such as time spent and political leaning of articles read. These data were gathered through the CivikOwl Chrome extension, featured on ProductHunt.
I was an astrophysics research intern at UC Santa Cruz in the summer of 2015 under Dr. C. Martin Gaskell, working with Jerry Hong. I learned how to program using Python and scientific computing libraries such as Numpy, Scipy, and Matplotlib, and developed a novel algorithm that analyzes data from the spectra of distant galaxies to draw conclusions about their temperature. Our abstract was published on the Harvard-NASA database and we were named national semifinalists in the Siemens Competition for Math, Science, and Technology.
During spring, summer, and fall terms of 2018, I was a tutor for the fastest-growing course at UC Berkeley, Foundations of Data Science, helping teach statistical inference techniques using Python. I held office hours, taught a small section, developed content with Jupyter notebooks and LaTEX, and graded assignments. I also got the opportunity to speak at UC Berkeley's undergraduate data science pedagogy workshop this summer as a student panelist, where I described my experience on Data 8 course staff to around 50 professors from universities across the United States. I'm now an Undergraduate Student Instructor for the class, teaching a section of 30 students and helping with various aspects of running the course.
I founded Data Science for India with fellow Berkeley students last May. I've largely been focusing on directing and participating in curriculum development, as well as interfacing with instructors on the ground. I devised and implemented a workflow for content development involving Jupyter and Git for coding content and Google Drive for worksheets. Our work over the summer teaching fundamental concepts of data science to 500 students in over 12 Indian high schools was recognized by the Institute of South Asia Studies at UC Berkeley. This summer, we piloted a curriculum tailored to students on "Data Literacy," and are working on bootcamp workshops targeted to teaching Python with an emphasis on data science for high school students.
In the spring of my freshman year, I joined Paradigm Shift, a venture that's working to promote computer science education in underserved high schools across the US, as a developer. I worked on content for workshops introducing computer science and a Python project that teaches basic concepts of artifical intelligence.