Jesse Tao

J[email protected] | (970) 310-9988 | Denver, CO |https://github.com/jesseptao

I am an electrical engineer turned data scientist that strives to improve the communities around me through my passion in programming and math. Using a variety of web development and data analysis tools has allowed me to collect and store geographical data, build applications and generate automated pipelines that have actionable insights. By combining my various technical skills, I am able to create innovative tools with a positive impact that seamlessly translate to the real world.

SKILLS

Languages: C/C++,  MATLAB, Python, SQL, MongoDB, HTML, CSS, PHP, Javascript, Git, Docker, Bash

Packages: Scikit-learn, Pandas, Numpy, NLTK, BeautifulSoup, Tensorflow, OpenCV, Flask, AWS, GCP

Data Visualization: Seaborn, Matplotlib, Folium, Tableau, Tensorboard

Modeling: Statistical Modeling, Regression Models, Classification Models, Time Series Forecasting

PROJECTS

Sales Forecasting, Small Business Hackathon

Collaborated with 3 UX designers, 2 software engineers, and another data scientist to integrate a sales forecasting model into the Toast POS platform over 3 days. Trained a multivariate recurrent neural network using previous sales and local event data to generate future sales predictions. Winner of the hackathon with over 120 participants decided by a panel of 3 judges all with multiple years of small business experience.

Spotify Recommender, General Assembly Data Science Immersive

Created a recommender model for Spotify that recommends new songs from new and less known artists based on what a user previously listened to. Compared songs using their audio files by transforming the audio file into MFCCs and taking the cosine similarity as well as calculating pairwise distances between songs using Spotify API's audio features call. Designed a web application so users can get recommendations as well as give feedback on the recommendations.

COVID-19 Vaccine Distribution, General Assembly Data Science Immersive

Worked with 3 other students in my cohort to predict the number of COVID-19 cases in each county in California using LSTM, ARIMA, and SARIMA models to improve vaccine distribution by allocating more vaccines to counties where outbreaks are predicted to happen. Built a web application with an interactive map and table to display the results of our findings.

Ames, Iowa Real Estate Analysis, General Assembly Data Science Immersive

Predicted housing prices in Ames, Iowa by exploring a dataset with over 80 housing features. Engineered features such as one-hot encoding and interaction terms to build a linear regression model to accurately predict home prices and help prospective home buyers determine if they are paying a fair price for their house. Winner of Kaggle competition in my cohort with lowest root mean squared error for predicted home values.

EXPERIENCE

TaoPokéMap – Web Development Lead            August 2018-Present

Tao Innovation Labs           Fort Collins, CO

done using the native Pokémon Go app

Pulse – Firmware Engineering Lead               August 2017-May 2018

CU Engineering Senior Design Project            Boulder, CO

device to help visually impaired individuals detect eye-level objects

STM32F4 microcontroller

on a Raspberry Pi

EDUCATION 

University of Colorado Boulder (CU)                                                                                       Bachelor of Science, Electrical and Computer Engineering, GPA: 3.2/4.0                        August 2014- May 2018

General Assembly

Data Science Immersive Remote                         November 2020-February 2021

models, web scraping, APIs, NLP, advanced supervised learning, unsupervised learning, SQL,

time series analysis, data engineering, deep learning, and Bayesian statistics.

learning techniques on these data sets to create projects that were presented to non-technical

and technical audiences.