Welcome to My Data Analytics Portfolio

Hi, I'm Hailey Thurston, a current student in Davenport University's Scientific Data and Analytics program, set to graduate in 2026. I created this website to showcase the projects I’ve been working on, highlight my growing experience in data science, and connect with others in the field.

My primary interests lie in analyzing data related to automotive systems, healthcare, and environmental health; areas where I believe data can make a real impact. Here, you’ll find examples of my work, from predictive models to data visualizations, all built with a focus on solving meaningful, real world problems.

Thanks for visiting!

My Portfolio

Welcome to my portfolio. Here you’ll find a selection of my work. Explore my projects to learn more about what I do.

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Areas of Focus

Data Insights

Automotive Analytics

My interest in automotive data stems from the growing role of data in improving vehicle sales, vehicle performance, safety, and maintenance.

Healthcare Data

Healthcare is a field where accurate, ethical, and timely data analysis can directly improve lives. I’ve studied and worked on datasets involving patient health indicators, treatment outcomes, and resource utilization. My focus here is on data driven decision making that supports better patient care, reduces operational inefficiencies, and upholds data privacy standards.

Environmental Health

I also have a strong interest in environmental health analytics, where data is used to understand the impact of pollution, climate, and public health trends. Whether analyzing air quality, water safety, or exposure risks, I aim to contribute to sustainable solutions through statistical analysis and visualization.

Technical Skills

Programming & Data Tools: Python (Pandas, NumPy, Scikit-learn), SQL
Business Intelligence: Tableau, Power BI
Data Visualization: Matplotlib, Seaborn, Plotly
Machine Learning: Regression, Classification, Random Forest, XGBoost
Software Tools: Microsoft Office Suite (Excel, Word, PowerPoint, Outlook)
Development Platforms: Jupyter Notebook, Streamlit
Data Analysis Workflow: Data cleaning, preprocessing, EDA, feature engineering
Model Evaluation: Accuracy, precision, recall, ROC curves, confusion matrices

My Approach

I approach every project with a problem-solving mindset. Whether it’s identifying hidden patterns, cleaning messy datasets, or building predictive models, I strive to turn data into actionable insights. I’m especially passionate about applying data analytics to real world systems where accuracy and impact matter most.

I’m always learning, experimenting, and refining my skills and I created this website to share that journey. Here, you’ll find my latest projects, research explorations, and practical applications of what I’ve learned so far.