Data Analyst engaging in the world of raw data with experience in data pipeline, ETL, visualizations and web development from
UC Berkeley’s Data Analytics and Visualizations Bootcamp. Avid curiosity in finding solutions backed up by dedicated work ethic
in synthesizing information from unrefined data to succinctly depict a story with elegant visuals and thought-provoking analysis.
Proficient knowledge in various Python and JavaScript visual and statistical libraries with background in Machine Learning modules.
Recent Data Analysis and Visualization Bootcamp graduate ready to utilize newfound skills with discipline and resolute communication
to achieve creative solutions. Developed dashboards and many interactive visualizations including Traffic, Weather Patterns,
Hotel Destinations, Earthquakes, Cryptocurrencies etc.
I am a :Ready to Engage: Data Analyst with a passion for visual storytelling and disciplined work ethic. My interests are in Data Management, ETL, Dashboards, and Machine Learning. Some of my personals enjoyments include FPS games, Japanese Media/Content and Badminton. I enjoy learning about the evolution of computer hardware specs. I enjoy listening to Metal/Rock, Drum n Bass Mixes, Jazz/Hip-Hop/Rap. I am currently volunteering at the Elk Grove Food Bank.
Data Analytics and Visualizations Bootcamp Graduate
Fast-paced, dynamic program that covered the specialized skills for the booming field of data, including: Intermediate Excel, Python, JavaScript, HTML/CSS, API Interactions, SQL, Tableau, Fundamental Statistics, Machine Learning, R, Git/GitHub, and more. Learned from skilled instructors and gained real-world experience by collaborating with peers on complex projects. Built a comprehensive portfolio along the way to tap into the industries.
B.A. Global Studies
Minor in Statistics, Japanese and Asian American Studies.
Participated in Intramural Badminton and Japanese Language Club (JLC).
Worked part-time as a Community Service Officer (CSO) for 4 years.
Displayed summary visualizations of car accidents in California Counties on a user-input interactive dashboard using Plotly.js, HTML, and CSS with AJAX jQuery and SQLAlchemy from a locally hosted PostgreSQL US Car Accidents Database. Modeled Accident Severity prediction for a user-selected California County using Decision Tree Classifier with various features and Severity as the target.
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Predicted credit risk with various machine learning algorithms using Python to monitor profiles and validate candidates for lending loans. Utilized and compared various machine learning models with trained and tested data such as Random Oversampling and Balanced Random Forest Classifier to select best-fit model of accuracy and precision
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Mapped earthquakes from the last seven days on an interactive map dashboard using JavaScript, HTML, and CSS with Flask App Utilized Leaflet.js API to populate recent earthquakes on a layered map with US Geological Survey GeoJSON data rendered with D3.js library hosted on a local server
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Performed ETL process and uploaded Reviews Datasets to an Amazon Relational Database Service (RDS) instance in the cloud through PostgreSQL. Utilized PySpark functions to perform statistical analysis of select reviews ("Vine") on video game reviews on Amazon.
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Created a live dashboard to showcase user-selected bacteria samples and statistics with interactive visualizations from JavaScript with development and debugging Plotted bar charts and a gauge counter using Plotly.js with D3.js event handlers to fetch external bacteria sample data .
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The Election Analysis Project aims to showcase the election auditing process for the Colorado congressional districts. Tom and Seth have asked an aspiring data analyst to help find the total votes, candidates, candidate votes, and the winner of the election.
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An analysis of the current and retiring employees in the Pewlett-Hackard Company.
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Trends and insights from various types of Kickstarters in order to help kickstart a friend's theatre campaign. Utilized Advanced Excel formulas and Pivot Charts to Analyize successfull kickstarters.
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Helping travelers pick the best time for vacation based on weather data from cities. Create visual trends of weather patterns in 500 randomly selected cities from around the world.
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Helping analyze school testing results to allocate district budgets.
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Create line, bar, scatter, bubble, pie, and box-and-whisker plots using Matplotlib. Add and modify features of Matplotlib charts. Add error bars to line and bar charts. Determine mean, median, and mode using Pandas, NumPy, and SciPy statistics.
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