Zachary-Raup

Data Science Portfolio

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Zachary Raup

Link to CV:

About Me

Welcome to my data analyst portfolio. I graduated Summa Cum Laude from Kutztown University with a bachelor’s degree in Physics, driven by an insatiable curiosity and a passion for data-driven exploration. Throughout my academic journey, I specialized in data analysis and modeling, particularly in the realms of exoplanets and binary stars. This experience not only deepened my understanding of complex datasets but also honed my skills in extracting meaningful insights.

Professionally, I have developed robust capabilities in Python for data analysis, leveraging techniques such as exploratory data analysis, data cleaning, and statistical modeling. I am proficient in SQL querying, adept at managing and extracting insights from large datasets to support data-driven decision-making. Additionally, I possess advanced skills in data visualization using Tableau and Power BI, creating insightful visualizations that effectively communicate findings and support strategic initiatives.

I am dedicated to applying my expertise in Python, SQL, and data visualization tools to solve challenging problems and contribute meaningfully to data-driven projects. I thrive in collaborative environments and am committed to continuous learning and professional growth in the dynamic field of data science.

 

 

Project 1:

Utilizing MCMC in Python to Explore the Parameter Space of an Exoplanet Transit

Project Overview

This research project focuses on modeling the transit of exoplanets across stars using the Python package ‘batman’. The objective was to accurately predict changes in stellar brightness during these transits, validated against photometry data from the CR Chambliss Astronomical Observatory (CRCAO). Methodologically, a physics-based model was developed and evaluated using a log likelihood function to fit observational data. The Markov Chain Monte Carlo (MCMC) algorithm, facilitated by ‘emcee’, enabled exploration of parameter uncertainties such as planet radius and transit timing. Visualizations created with matplotlib included light curves, histograms of parameter distributions, and a corner plot illustrating parameter correlations. Presenting findings at the 241st AAS meeting highlighted contributions to understanding exoplanet transit dynamics, crucial for advancing knowledge of planetary systems beyond our solar system.

Skills Applied: Python (pandas, matplotlib, numpy, emcee, & batman), Jupyter Notebook, and Excel

Image 1: TOI-4153 modeled lightcurve

Light curve of TOI-4153 data (CRCAO) taken in a Blue (B) and Infrared (I) filter. The model is built using the Python transit modeler package ‘batman’. The parameters of the model were determined using the Markov Chain Monte Carlo algorithm and known parameters taken from the ExoFOP database.

 

Project 2:

Insights into Dog Behavior: Analyzing Dognition Data with MySQL

Project Overview

The goal of this project is to utilize MySQL queries to perform analysis of trends and relationships embedded within the Dognition database. Developed as a fundamental component of the ‘Managing Big Data with MySQL’ course from Duke University, the project focuses on refining and applying skills in data cleaning, sorting, and employing advanced analytical techniques using SQL. By exploring large datasets such as the Dognition database, the project aims to uncover meaningful insights into canine behavior patterns and preferences, leveraging robust data management practices to extract actionable intelligence for further research and practical applications in understanding and enhancing dog-human interactions.

Skills Applied: MySQL, Writing Queries, Data Cleaning, and Big Data

Image 2: Top States by Number of Dognition Users

 

Project 3:

Interactive Animation of Museum Visitor Paths and Hourly Room Traffic in Tableau

Project Overview

The project was undertaken as part of the ‘Data Visualization in Tableau’ course in Data Camp, where I applied advanced data visualization techniques to transform raw museum data into a meaningful and engaging interactive animation. By leveraging Tableau’s powerful features, I was able to create a comprehensive and user-friendly tool that highlights key patterns and trends in museum visitor behavior by the hour. This project not only demonstrates my proficiency in using Tableau for data visualization but also underscores the practical application of these skills in real-world scenarios.

Skills Applied: Tableau, Data Visualization

Image 3: Common Musuem Visitor Paths

 

Zachary’s Portfolio
Project 1: Utilizing MCMC in Python to Explore the Parameter Space of an Exoplanet Transit
Project 2: Insights into Dog Behavior: Analyzing Dognition Data with MySQL
Project 3: Interactive Animation of Museum Visitor Paths and Hourly Room Traffic in Tableau