About
Data science professional with 5 years of experience spanning analytics, machine learning, and data visualization. UC San Diego B.S. Data Science graduate with hands-on research experience at Scripps Institution of Oceanography and the Halicioğlu Data Science Institute, plus industry experience at Deloitte. Passionate about turning complex datasets into actionable insights — from analyzing 70+ years of climate data to building award-winning autonomous vehicle systems.
Gino Angelici
Data Science Professional
Education
UC San Diego
Sep 2021 – Jun 2025B.S. Data Science
San Diego, CA
Coursework
Technical Skills
// Languages
Python
SQL (PostgreSQL)
Java
C/C++
R
JavaScript
TypeScript
HTML/CSS
ROS2
// Libraries & Frameworks
PyTorch
TensorFlow
Pandas
Keras
Scikit-learn
XGBoost
Hugging Face
NumPy
PySpark
Statsmodels
D3.js
Three.js
React
Svelte
SwiftUI
// Tools & Platforms
AWS
Docker
Git/GitHub
Spark
Kafka
Airflow
Snowflake
BigQuery
Databricks
Tableau
Power BI
MongoDB
Google Analytics
Experience
Data Research Assistant
Sep 2024 – Jun 2025Halicioğlu Data Science Institute
Autonomous Vehicle Development
- Optimized gradient descent–based steering algorithms to improve cornering speed on a figure-8 track; maintained Docker environments for GPS and IMU integration across scaled car prototypes (1/10, 1/5, full-size).
- Won 1st place at Purdue University's premier collegiate full-size go-kart race, achieving 30 mph top speeds with autonomous emergency braking across varied weather conditions.
1st Place Winner
Data Research Assistant
Sep 2022 – Sep 2024Scripps Institution of Oceanography
- Built Python pipelines to analyze 70+ years of climate data from 60 coastal airports, applying sliding-window PCA, polynomial regression, and ridge regression to model correlations between low cloud cover and temperature trends.
- Collaborated with climate scientists to update a published paper; findings linked urbanization to reduced cloud thickness and elevated local temperatures.
Data Science Intern
Mar 2023 – Jun 2023Deloitte
- Analyzed U.S. Department of Health and Human Services data using XGBoost, ridge regression, and linear regression to identify behavioral traits predictive of substance abuse in young adults.
- Presented findings and actionable insights to senior Deloitte management using Seaborn and Plotly visualizations, demonstrating strong technical consulting and communication skills.