Naij Taylor

I'm a senior applied statistics major with experience in trend analysis, regression analysis , data pipelining, simulation building, r and python. My portfolio website is naijportfolio.com. It has in depth project breakdowns, and links to the project code.

I am a graduate with a Bachelor of Science in Applied Statistics from Middle Tennessee State University. My professional foundation was established during my time as a Summer Biostatistician Intern at the Vanderbilt Biostatistics Department. In this role, I developed an R-based simulation to evaluate a new statistical weighting method, which involved generating a dataset of 20,000 observations. My research led to the discovery of how stratification affects the precision of specific models, a finding that prompted the department to make stratification techniques the primary focus for the following year's research cohort.

In addition to my formal internship, I have completed several high-level technical projects. I engineered an ETL pipeline utilizing a Binance market API to model second-by-second Bitcoin price volatility, where I successfully leveraged a Cox regression model to predict trend continuance. Between June and August 2025, I focused on building a model to identify causal relationships in data. While this project remains unfinished due to data limitations, the causal inference code itself is largely complete. I have also explored human-centric AI approaches, specifically using Google Gemini's Deep Research to analyze player and team data for a sports betting model. Most recently, in December 2025, I used SQL to standardize nationality data and implemented Power BI to uncover disparities in Covid-19 mortality rates across different populations. Throughout these experiences, I have developed a versatile toolkit that includes Python, R, SQL, machine learning, and trend forecasting.

Applied statistics with a focus with supplemental background in general applied mathematics (calculus, differential equations, numerical analysis,etc)