Leveraging machine learning and Python to turn interesting yet messy and complicated data about the modern world into directly applicable insights. A self-starter with hands-on experience in diverse projects with a mix of systematic and inventive approaches, I excel in big picture critical thinking, extensive data collection and thorough quantitative analysis.Technical Skills:-Languages: Python, Golang, SQL, C++-ML&AI: NumPy, Anaconda, Sci-kit Learn, PyTorch, h20.ai, Scipy, Classification, Regression, Clustering, Deep Learning, Feature Engineering, PCA and Dimensionality Reduction, Multi-layer Modeling-Stats: Descriptive and Inferential Stats, Hypothesis Testing, Confidence Intervals, Time Series-Practical Skills: Jupyter, Pandas, Microsoft Office, Web Scraping, ETL processes, Faker, Data Visualization, Image Processing-Cloud: Microsoft Azure (certified)Experience:-Information Security Associate in the Cybersecurity Data Science department at Wells Fargo bank-Intensive Data Science Project-Focused Bootcamp @ Springboard overseen by experts in the field-Machine learning and cloud computing accreditation from Microsoft, Coursera, and Udacity, overseen by expertsSome achievements (more work is featured in my GitHub profile):-Unit tested corporate security scanners and AI tools, writing scripts to generate hundreds of rigorously constructed documents for the test environment, with results approved by senior engineers-Mapped the log4jscanner GitHub repo, updating the work of the google engineers who wrote it by noticing versions of the log4j vulnerability that their code missed, allowing me to give engineering guidelines and recommendations for my team-Built the highest accuracy model for predicting competitive viability for each creature in the game Pokémon, inventing original features (the “cindex” measure based on techniques from Natural Language processing) and two-stage random forest methods specializing in categorical variables (from h20.ai)-Created a competitive Pokémon dataset for Kaggle via extensive web scraping and data cleaning-Applied random forest to model ticket prices of 200+ US ski resorts, offering executive insights-Conducted t-tests on Kaggle medical data to analyze variations in charges for insured and uninsured patients-Utilized the Quandl API to calculate detailed 2017 financial informationLearning: Power BI, natural language processingPlease contact me with any employment opportunities in data science, data analytics or software development suitable for my skills!