Core Technologies: Python, MySQL, Spark, Tableau, Pandas, NumPy, Matplotlib, Seaborn, SciKitLearn, Anaconda, Jupyter Notebooks, Git/GitHub
Core Competencies: Data Storytelling, Applied Statistics, Machine Learning, Natural Language Processing, Classification, Regression, Clustering, Time Series Analysis, Anomaly Detection
Primary Focus: Data Analytics
I’m a results-driven data scientist who served in the US Marine Corps and have an extensive background in intelligence operations and analysis. I’m skilled at finding trends in large data sets, producing actionable insights, and providing visual aids to back my findings. In addition, I have the ability to prioritize tasks, lead and collaborate with teams, and successfully convey findings. Ultimately, I’m dedicated to producing the best possible products and promoting data-driven decision-making to improve organizations.
My Capstone Project: Healthcare Fraud Buster
Elevated healthcare costs due to provider fraud is a growing concern for millions of Americans. Our mission is to combat provider fraud and create a more affordable and accessible healthcare system. CMS(Center for Medicare & Medicaid Services ) provides publicly available data about Medicare. We acquired over 500,000 rows of Medicare Data from Kaggle. We aim to predict potentially fraudulent providers, uncover key indicators of fraud, and understand fraudulent patterns within their claims utilizing various classification models. We’re committed to making a positive impact on the healthcare system, by reducing insurance premiums and ensuring high-quality, affordable healthcare.
