Data Science

As a backend engineer and data scientist with a B.S. in Computer Science from MSU Denver (2025), I have gained hands-on experience through academic projects, personal initiatives, and leadership roles. My work focuses on building secure, scalable systems using technologies like Kotlin, Ruby on Rails, Python, Rust, AWS, and Kubernetes. Below is a summary of my key experiences. 🔍 Professional Highlights Technical Leadership and Development: Led teams in developing mobile and web applications, integrating APIs, and ensuring secure, accessible designs. Data Science and Machine Learning: Built predictive models and interactive dashboards for real-world datasets, achieving high accuracy in classifications. Cloud and Ethical Systems: Founded initiatives for ethical AI and cloud-native solutions, leveraging AWS credentials and open-source collaboration. Agile Methodologies: Managed projects using Agile, Feature-Driven Development (FDD), and DevOps practices for efficient delivery. 📦 Experience Summary Lead Developer, Personal Portfolio Site: A Meta Adventure in Self-Promotion August 11, 2025 – August 14, 2025 ...

From May 2025 to July 2025, I completed a 5-week, 45-hour capstone project for the IBM Data Science Professional Certificate as part of my B.S. in Computer Science from MSU Denver. This project analyzed SpaceX launch outcomes, building a full data science pipeline to predict mission success using Python, machine learning, and interactive dashboards. 👉 View IBM Data Science Specialization Certificate 👉 View GitHub Repository 🔍 Project Highlights Designed a Python-based data science pipeline across five weeks, integrating SpaceX REST API and web scraping. Built interactive dashboards with Plotly Dash and Folium for launch site analysis. Achieved >90% accuracy in predicting launch outcomes using machine learning classifiers. Delivered a technical presentation summarizing methodology and insights. 📦 My Role: Data Scientist Pipeline Development: Built and executed a data science workflow, from data collection to model deployment. Data Analysis: Performed web scraping, data wrangling, and exploratory analysis with Pandas and SQL. Visualization: Created interactive dashboards using Plotly Dash and Folium maps. Modeling: Developed and tuned machine learning classifiers (Logistic Regression, Decision Trees). Presentation: Authored a technical report and presentation for Coursera evaluation. This role strengthened my skills in data science, machine learning, and data visualization. ...