🎓 Education
- Master's student in Information and Data Science at UC Berkeley (Expected Graduation: Dec 2023)
- B.A. in Data Science with Honors
💼 Skills & Certification
- Languages: Python, SQL, NoSQL, ORM, R, Java, JavaScript, C, C++, CSS, HTML
- Libraries/Frameworks: H2O AutoML, MapReduce, NumPy, Pandas, Scikit-learn, SciPy, Matplotlib, Seaborn, Plotly, Flask, TensorFlow, Keras, Django, NLTK, Git, SQLite/MySQL/PostgreSQL, Database, ETL, PyTorch, Schema, Hadoop, AWS, EC2
- Techniques: Tableau, PowerBI, MatLab, Apache Spark, APIs, Excel (Pivot Table, VBA Scripting), Neural Networks (CNN, RNN), KNN, EDA, Clustering, Time Series, NLP, XGBoost, Linear/Logistic Regression, SAS/SPSS, GLMs, Decision Tree, Random Forest, Skip-Gram, Hypotheses Testing, A/B Testing, GCP, SVM, Docker, LLM, Parallel Computing, Naive Bayes, Causal Inference, Descriptive/Inference Statistics, Qualtrics, Parametric Test, Experimental Design, Feature Engineering, Azure Databricks, Data Visualization, Dimensionality Reduction, Anomaly Detection, Computer Vision
- Certification: Recommendation System with Python, ML & AI; Advanced Python: Databases; SQL Programming
💻 Experience
- Quantitative Analytics Intern, Wells Fargo (Jun 2023 - Aug 2023)
- Data Scientist Intern, Applied Materials (May 2022 - Aug 2022)
- Data Consultant, Grocery Outlet Holding Corp (Jan 2022 - May 2022)
- Marketing Intern, Applied Materials (May 2021 - Aug 2021)
- Data Consultant, by Humankind Inc. (Apr 2021 - Jun 2021)
📂 Projects
- San Francisco New Housing Development Outlook (UC Berkeley School of Information)
- Constructed a Neural Network model to offer insights into SF's new housing development trends.
- Twitter Post Credentials' Impact on Perceived Credibility (UC Berkeley School of Information)
- Designed a conjoint experiment to determine attributes influencing the perceived credibility of online posts.
- Spotify Content-Based Recommender (UC Berkeley)
- Created a content-based music recommendation system using Spotify’s Web API.
- Fleet Optimization (Honda R&D Americas, LLC)
- Developed a scheduled MaaS simulation algorithm to optimize fleet capacity using Honda's MicroTransit API.
- BEACO2N (UC Berkeley Department of Chemistry)
- Captured and analyzed emission readings of supersite nodes.
- Built a real-time map visualization for sensor telemetry.
🌟 Passion
- Passionate about transforming data into meaningful narratives.
🔍 Exploration
- Always exploring new data methodologies and open to collaborations.
🔗 Connect
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent