At CNA, I work on a number of concurrent projects in support of the United States Navy, primarily relating to maintenance and force readiness. My work spans across all phases of the data science lifecycle, including collecting data, data wrangling, dashboarding, statistical hypothesis testing, implementing machine learning algorithms, and presenting results to senior leaders.

In Fall 2021, I was the GSI for a pedagogy course which is offered to first-time (u)GSIs in statistics and data science. I led a section of about 25 undergraduates, during which we discussed teaching practices and work through practical activities. I highly enjoyed relaying my experiences as a uGSI to help foster the next cohort of teachers. In addition to leading the section, I graded homework, and assisted the professor in lesson planning for the course, as this was its first offering.In Spring 2022, I was head GSI for Data 102: Data, Inference, and Decisions, which is a senior-level course covering advanced topics in data science and machine learning, such as neural networks, reinforcement learning, causal inference, and Bayesian modeling. In addition to teaching lab and discussion sections, I worked with the professors to ensure a smooth course delivery by handling most logistics.

I continued work with CCI as a graduate student. In the fall, my first project was to help California's Department of Housing and Community Development streamline their process for collecting data from the state's ~500 jurisdictions. I created tools for quality control by tracking errors in data submission, and provided suggestions to HCD to ensure the data the department receives is consistent and accurate.In the spring, I started on a new project, working to rebuild the organization's displacement measure for the state of Utah. I revamped the data processing pipeline and made key decisions over feature inclusion and other modeling strategies for our BART model.

In Summer 2021, I was co-instructor for Data 100—a course which "explores key areas of data science including question formulation, data collection and cleaning, visualization, statistical inference, predictive modeling, and decision making."I developed the syllabus, formulated policy, and managed about 20 staff for an offering of over 350 students. My favorite contribution was recording four new lectures for the course, on topics ranging from the bias-variance tradeoff to clustering (my favorite!). I also worked with our staff to update our assignments and ensure the best possible experience for every student.

For three semesters, I was an undergraduate student instructor (uGSI) for Data 100. I led discussion sections, assisted in reviewing and releasing assignments, wrote and graded exams, as well as helped students in remote video office hours and through our online forum. Additionally, in the Spring 2021 semester, I recorded videos that walked students through the weekly lab assignment.

This was my first paid course staff role, following two semesters of "academic interning." My role as a tutor was to grade homework, as well as hold office hours to help students with assignments. This was the semester where everything changed—following the transition to virtual learning, I held small group sessions to review content with students that were falling behind in the course. I'm really thankful for this experience as it prepared me for the uGSI and instructor roles which I would take on later.

For most of undergrad, I was a student assistant in the Facilities branch of UC Berkeley’s Athletics Department. I prepared Haas Pavilion for games and practices by setting up and breaking down basketball hoops, volleyball nets, the scorers’ table, and other equipment. I trained new workers to do these tasks, both on-the-job and through instructional videos that I created. I was also a ballboy for a few Pac-12 volleyball games in 2019. I really enjoyed doing the behind-the-scenes work that supports the college basketball that I enjoy so much!

Throughout my senior year, I worked as a research assistant with Berkeley’s Center for Community Innovation, under the supervision of Dr. Karen Chapple. Throughout my time at CCI, I have bounced around various projects:- Building a model to determine the factors affecting the construction of Accessory Dwelling Units (ADUs) in California. My role here was to collect and join different datasets to feed into the final regression model.- Querying a database of all parcels in California to present in a policy brief on zoning reform and ADU construction. I was fortunate enough to be listed as a co-author, and you can read the brief from the Terner Center for Housing Innovation here. Despite our efforts, the bill failed.- Mapping ADU construction patterns. I worked on the interactive map at www.aducalifornia.org, and I created the maps published in this report, using ArcGIS.- Wrangling data from large, proprietary datasets, such as Zillow’s ZTRAX data on property transactions, and Infogroup’s consumer database. This was low-level work that fed into various projects, including a measurement of displacement across US cities, the construction of a subsidized housing database for California, and a report on COVID-19's impact on minority-owned businesses in the Bay Area.

After following a lead from one of my planning professors, I assisted PhD candidate Teddy Forscher of the Transportation Sustainability Research Center with his research project on e-commerce shopping habits, the environment, and COVID-19. I cleaned and re-structured the results of his survey pre-test to guide the creation of his final survey, and then did the same with the final survey results to make the data easier to analyze. I also pursued different avenues of data collection, such as tracking numbers for online order shipments.“You’re the best data wrangler I know.” - Teddy

My summer job throughout high school and college was with the South Orange Recreation Department. My primary role was at the front desk of the community center as a customer-facing representative. I enrolled customers in activities, answered the phones, helped set up the building for events, and pointed many basketball players towards the water fountains.One summer, I was also a gate attendant at the community pool, where I scanned in members and guests. Before working in the office, I enjoyed being involved in various youth sports organizations—I umpired intramural baseball games (ages 9-13), and operated the scoreboard for middle school travel basketball games.

I worked on team with other students that attempted to find undervalued college basketball players, project their performance to the NBA, and determine whether or not they would be a good fit for the Warriors roster.