Phillip Busko

Washington DC

443-***-****

adbv8u@r.postjobfree.com

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Data scientist and software engineer with background in physics, data mining, database administration, and web development. Interested in all realms of artificial intelligence and modelling; including machine learning, scientific analysis, game AI, computer vision, neural networks, NLP, robotics, etc.

Technical Skills

Python, SQL, C#, Javascript, HTML, SASS

Pandas, Scikit-learn, Plotly, XGBoost, Django, React

Visual Studio Code, Jupyter, MS SQL Server, PostgreSQL, AWS Console

Technical Projects

Filmophile - Github

Scraped data from movie information and streaming service websites with selenium package

Engineered several features as a mix of the same column from different data sources, applying one-hot and multi-hot encoding to categorical columns

Searched for the best classifier among: logistic regression, naïve bayes, KNN, random forest, SVM, xgboost

Tuned support vector machine (sklearn sgdclassifier) to improve accuracy by 6%

Regression for Pricing of Lego Sets - Github

Scraped Lego set data with requests and beautifulsoup libraries

Tuned a linear regression regularization model to predict the price of a new Lego set with a R2 of 0.86

Preserved the interpretability of beta-coefficients in order to construct a symbolic mathematical model

Classification for Profitability of New Lego Sets - Github

Processed the columns of the Lego data set to engineer new coarse-grain features and the target variable

Trained logistic regression with different solvers and regularization for a baseline accuracy of 78%

Tuned a random forest with grid search of hyper-parameters to improve accuracy to 80%

Changed the balance of input classes with the imblearn pipeline using under sampling and SMOTE

Professional Experience

Data Science Fellow, Flatiron School, Washington DC

2019 – 2019

Learned fundamentals of data science practice and theory using Python in Jupyter notebooks

Studied pandas dataframe, website scraping and APIs, exploratory data analysis, statistical inference, supervised learning classifiers, unsupervised learning clustering, and natural language processing

Collaborated on 7 different projects, each focusing on a new area of study

Software Engineer, IT Innovative Solutions, Gaithersburg MD

2018 - 2019

Used SQL Server Management Studio to import data files and run processing scripts

Learned React, Angular and SASS to build client-side applications

Implemented a RESTful server’s API endpoints in C#

Founder & CTO, Lige Ma, Baltimore MD

2015 - 2017

Self-taught full stack development and deployment: Django, PostgreSQL, jQuery, Amazon Web Services

Website features include web crawlers for soccer data, user authentication, global chat using web sockets, PayPal monetization scheme, user-to-user messaging, and thin client paradigm for the game state

Software Engineer, Audacious Inquiry, Baltimore MD

2012 - 2014

Learned SQL and SSMS and ultimately created stored procedures dynamically

Increased the correctness of synthesized HL7 inpatient hospital visits from 60% to 90%

Administered databases (2NF, star schema) utilizing diagrams, partitioning and backups

Built extract-transform-load (ETL) packages for loading databases and processing existing data

Authored extensive software documentation to on-board new personnel

Engineer, Sensor Concepts & Applications, Glen Arm MD

2010 - 2012

Learned C# and Visual Studio, and began contributing to production code within 3 weeks

Parsed various vendor data file formats, including xml and binary, and converted them to a common data structure for visualization and analysis of radiation spectra

Created MCNP (Department of Energy tool) high-energy physics simulations that mirrored real-life experiments

Education

Boston University, Boston, MA

Masters Physics – May 2008

University of Maryland, College Park, MD

B.S. Physics, magna cum laude – May 2004

B.S. Computer Science – May 2004

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