Hi, I'm Tyson!
Data Analyst
About
I graduated, in May 2020, from the University of Vermont (UVM) with an M.S. in mathematics. During my time at UVM — in addition to my student role — I taught undergraduate math courses to 134 students over four semesters. I also did research under my advisor, James Bagrow, in the Vermont Complex Systems Center. My thesis focused on modeling [textual] information flow in online social networks and utilized large-scale simulation, data collection, and data analysis to validate our model. I collaborated with researchers from the University of Adelaide and led our work to journal publication in Entropy .
After graduating, in the midst of the pandemic, I needed some time to re-energize and reflect before identifying a career path. During this time, I've been expanding my technical skills and developing a portfolio of practical (tackling common business problems), end-to-end projects to complement my academic work. I am joining MediaAlpha as a Data Analyst in July 2021.
I am a native Vermonter, and also obtained my B.S. in mathematics from UVM. Outside of work, my interests include: puzzles (Sudoku variants), cooking (soup & chili connoisseur), hiking, and biking.
Portfolio
I've built end-to-end data applications for: social media & technology, customer insights, and financial risk assessment. Check out a few of them below or browse more on my Github.
My spotify
in progress- Developed an ELT data pipeline, using Python, to analyze my daily Spotify activity.
- Created visualizations using D3.js and built the application front-end with HTML/CSS/JavaScript.
Ice cream data dashboard
- Assessed product performance and identified common complaints for ice cream companies — potentially increasing customer retention — by parsing customer reviews with spaCy and applying NLP methods: n-grams, sentiment analysis, and topic modeling
- Collected all customer reviews (20,000) from four company websites using Python and Selenium for web scraping
- Created interactive visualizations – allowing for product comparison and trend analysis – using Highcharts and R, and built a web application using R Shiny
Twitch tastes
- Built a collaborative filtering recommendation system to suggest live streamers to Twitch.tv users, potentially increasing daily hours watched
- Collected data on 280,000 user-streamer follows, via the Twitch API, to train our model on
- Built a web application and RESTful API using Flask and deployed with Heroku
- Used NetworkX to visualize and identify communities, further informing our recommendations
LendingClub loan default prediction
- Developed a model to predict probability of default for loans on LendingClub
- Used scikit-learn to develop, and optimize the parameters of, our feature selection and modeling pipelines
- Used cost-sensitive metrics for imbalanced data and selected the best model from several classification models: logistic regression, KNN, random forests, XGBoost, and neural networks
Information flow in social networks (M.S. thesis)
- Developed a novel measure and model of written information flow in online social networks
- Estimated that a user’s text can be predicted with up to 95% accuracy using their social ties
- Utilized a Linux cluster and Python to perform large-scale simulations (generating 100GB of data) and collect 30 million tweets to validate our proposed methodology
- Led a team of five international researchers to publish our results
Skills
Languages
- Python
- R
- MATLAB
- SQL
- HTML/CSS
- JavaScript
Libraries
- pandas
- NumPy
- Matplotlib/seaborn
- scikit-learn
- TensorFlow/Keras
- NetworkX
- Flask
- R Shiny
- D3.js
- Highcharts
Analytical
- Social network analysis
- NLP
- Recommender systems
Teaching
At UVM, I taught Fundamentals of Calculus I (MATH 019) and Applications of Finite Math (MATH 017).
My teaching pageContact
To get in touch, send me an email at pondtyson@gmail.com or reach out on LinkedIn.