About
Hello, my name is Albert Carreno. I’m a recent UCLA Statistics & Data Science graduate looking for hands-on data science experience. I enjoy applying data-driven, quantitative methods to tackle complex problems. I am especially skilled at using machine learning techniques for predictive modeling and producing actionable insights. For professional inquiries, please reach out via email: bertcar1402@gmail.com.
Education
University of California, Los Angeles | Los Angeles, CA | B.S. in Statistics & Data Science | Minor in Film & TV | 3.7 GPA | Sept 2021 - June 2025
Darien High School | Darien, CT | 3.72 GPA | Aug 2017 - June 2021
Relevant Experience
EEOC | Summer Data Analytics Intern | Washington D.C. | June 2024 - Sept 2024
Constructed a classification model in R using multinomial logistic regression with elastic net regularization that categorized over 100,000 job titles.
Reduced time and energy required to estimate the public burden for filing EEO-1 reports.
Delivered results and explained methodology in a 20 minute presentation to the entire OEDA department.
BSA | Baseball Consulting Team | Los Angeles, CA | Sept 2024 - June 2025
Built a gradient boosting ML model that predicts pitch type with 95.4% accuracy based on variables that included spin rate, vertical break, and pitch trajectory for the UCLA Men’s Baseball Team.
Led a team that created an ensemble majority vote model in R that blended neural networks, random forests, and gradient boosting to predict batted ball outcomes with 88.3% accuracy.
BSA | Data Journalist | Los Angeles, CA | Sept 2022 - June 2024
Wrote data driven articles for Bruin Sports Analytics, UCLA’s undergraduate sports statistics group.
Incorporated statistical methods to tackle sports topics such as predicting NHL playoff outcomes.
After performing basic EDA in Excel, methods often included multivariate linear and logistic regression in R.