Familiar with Data Queries, Statistical Analysis, and Sampling, Regression and Correlational Analysis, Classifiers. Also proficient with Data Visualization, Cleaning, Consolidation, and Smoothing. Can use libraries including NumPy, SciPy, Math, Matplotlib, and some Pandas.
Very familiar with markdown (including LaTeX) and code implementations of notebooks.
Can use Lightroom, Portfolio, and Spark excellently, some experience with Photoshop
Fundamentals of Number Theory, Induction, Cryptography, Graph Theory, Set Theory Grade: A
Statistical Analysis, Table Manipulations, Research Methods, Bootstrapping, Confidence Intervals Grade: A+ Percentile: 99.5
Able to communicate and relay ideas or information concisely and accurately to superiors, co-workers, and subordinates
Work well on feet and under pressure, as well as ability to revise action plan to accommodate changing demands
Can use resources such as materials, energy, etc. effectively and efficiently, and can also manage time spent between projects
Able to solve not only straightforward, logical problems, but also more complex issues which require out-of-the-box, unconventional ideas
Able to notice small details and/or errors, especially in the context of large projects
I am a devoted recent UC Berkeley graduate (Fall 2024). During my academic tenure at Berkeley, I focused my studies on the nexus of Data Science, Computer Science, Cognitive Science, and Psychology, while maintaining a 4.0 across all four fields of study. I have expertise in Python, SQL, Ruby, Java, and JavaScript, and have particular focuses on Machine Learning, Data Science, Deep Learning, Natural Language Processing, and Full-Stack Development. Through hands-on experience as a Technical Project Manager at UC Berkeley and internships at Blackhawk Network and Liberty Mutual, I’ve learned to lead teams, solve complex problems, and create scalable digital products. I thrive on integrating emerging technologies—like computer vision and advanced NLP—into practical applications, and I’m driven by a commitment to teamwork, adaptability, and attention to detail. Ultimately, my goal is to leverage my broad academic foundation and real-world experience to build robust, solutions in the tech industry.
Quadruple majoring in the College of Computing, Data Science, and Society and the College of Letters & Science at UC Berkeley. I have been involved with several on-campus organizations such as the Mathematics Undergraduate Student Association, Data Science Society, and Data Science Modules
- Statistics: GPA: 4.0 | Units: 238.2 | Class Rank: 1
- Manage 10+ teams of 3-5 developers each, using Jira to track progress, allocate tasks, and ensure timely deployment
- Develop curriculum for 90+ courses across 45+ departments, impacting 13,000+ students, aligning materials with faculty goals
- Build and maintain GitHub Action workflows, automating contributions to streamline development and improve reproducibility
- Coordinate the building of Jupyter assignments for courses with 500+ students, integrating Python into non-technical subjects
- Design data-driven assignments for Environmental Studies courses, developing coral preservation projects in French Polynesia
- Engineer a full-stack application to handle +10,000 daily financial transactions from clients and update respective databases
- Master JavaScript, React, Next.js, Java, SpringBoot, Postman, and CORS as the tech stack and fully integrate the technologies
- Implement Server-Side-Rendering solution to improve the speed of web-based applications to better the experience of customers
- Design a scalable REST API to allow for stateful communication between the user interface, backend logic, and databases
- Create modular applications with explicit documentation for improvement in scalability, deployment, and maintenance
- Work with SQL in Snowflake, SAS, and Jupyter to efficiently query massive databases with over 60B entries for relevant data
- Employ robust distributed computation, storage, and data processing to build intuitive classification models to recommend concrete business strategies in unique geographical regions in the U.S. based on business and publicly available data
- Create a project scaffold to increase further computational efficiency and decrease operational costs for future usage/adaptation
- Utilize Partial Component Analysis, along with Agglomerative Clustering, Random Forests, and Multiple Linear Regression to build multiple models that predict the best business strategy by geographic region to drive profitability and growth of business
- Developed and deployed Data 101 assignments using GitHub Actions for CI/CD, Ruby, and Jekyll for website management
- Designed data engineering pipelines with Python, Jupyter notebooks, and cloud platforms (AWS, GCP) to teach ETL, data ingestion, transformation, transactions, query optimization, and use structured, semi-structured, and unstructured databases
- Integrated scalable data solutions (S3, BigQuery, Spark) into the curriculum, allowing students to gain industry-aligned experience
- Automated grading workflows with GitHub Actions, Otter-Grader, and Gradescope, improving efficiency for 300+ students
- Build an end-to-end webcam-based application to translate sign language in real-time to English using Deep Learning and NLP
- Implement Video Visual Transformers to predict word-level labels from video input of ∼2000 classes and 100+ different sources
- Engineer BERT additive model to augment predictions based on relative occurrence frequency with previously predicted words
- Engineer a recommendation algorithm to generate a playlist based on a given song by a user, selected from the Spotify library
- Use vector embedding to generate recommendation scores between songs based on features from Spotify API and date/artist
- Build POC web application and UI based on a limited dataset from a collection of multiple volunteers personal Spotify data
- Implement use of Spotify API; allowing users to sample songs within the application for manual verification of performance