Data Scientist
MSc Bioinformatics
I am continually in search for underlying patterns that illuminate hidden connections between seemingly disparate entities. My passion lies in uncovering solutions to challenging problems and turning complex information into clear-cut, actionable statements.
Download my cv or contact me if you’d like to share ideas.
Advanced statistical models in Python and R
Deduction of underlying probability distributions
Merging scientific methods & divergent thinking
Mastery of ggplot2, matplotlib, and Tableau
Sentiment analysis of complex customer data
End-to-end pipelines for easy data analysis
Here are a few select projects I’ve completed. The code can also be found on my github account
Vast improvement and refactoring of the previous Pet Adoption Time project. Incorporated image feature extraction, image metadata, entity sentiment, and text mining to the initial model
Skills: Python, Keras, LightGBM, Google Vision, Google NLP, Convolutional Neural Network, TF-IDF
Front-end web app visualizing and analyzing artists’ musical audio features through Spotify’s Web API. Identifies the most unique and the most ordinary tracks for an artist and provides recommendations for other similar songs
(Note: Please allow a few moments for Heroku to spin up the initial dyno)
Skills: Python, App Development, CSS, API, Data Visualization
Extracts deep image feature representations and merges the content of one image with the style of a second images
Skills: Python, TensorFlow, Computer Vision, Convolutional Neural Network
Increasing profitability of a bakery through Association Rule Learning
Skills: R, Association Rule Learning, Market Basket Analysis
Predicting pet adoption time using a decision tree ensemble model
Skills: Python, Supervised Ensemble Learning, XGBoost, Decision Trees, χ2 Analysis, EDA
Predicting polarity of user reviews through text mining of IMDB reviews without NLTK’s SentimentAnalyzer library
Skills: Python, NLP, Sentiment Analysis, Text Mining
An XGBoost ensemble model predicting house prices of the Boston real estate market
Skills: Python, Imputation, Regression, Feature Engineering, XGBoost, Ensemble Models
Predicting survival of passengers aboard the Titanic using binary classification machine learning
Skills: Python, EDA, Feature Engineering, Imputation, Classification, Neural Networks
A collection of cool things I’ve worked on for my personal enjoyment >>
An interactive infographic highlighting the UFC’s Anti-Doping Program
Web scraping, archiving, and search retrieval of monsters scraped from DND Beyond
Adding GIFs to a Valence (Song Positivity) Analysis of Gorillaz Discography