Official Resume – Hannah Sky Gonzalez

Education

Expected Graduation: Spring 2027

B.S. Data Science & B.A. International Business

University of California, San Diego

Coursework: Systems for Scalable Analytics, Probabilistic Modeling & Machine Learning, Representation Learning, Data Structures & Algorithms, Data Management, Data Analysis & Inference, Econometrics, Product Marketing & Management.

Activities: Women in Business, Recreational Basketball, Mentorship, and Toastmasters.

Experience

June 2026 – Aug. 2026

Data Science Intern

JPMorgan Chase & Co. · Jersey City, NJ

Built a machine learning model utilizing GPT and LightGBM that mapped new and updating regulatory text to impacted teams, optimizing the manual review process for the compliance department.
Developed a candidate retrieval system using Word2Vec embeddings and cosine similarity to filter thousands of regulatory records across 16 business lines and 247 sub-lines.
Achieved 90% recall and 97% peak accuracy through adaptive threshold calibration and a LightGBM reranker, ensuring complete coverage for human reviewers.
Overcame extreme data sparsity with candidate generation and global fallback mechanisms for business lines with fewer than 10 historical examples.

Nov. 2025 – Present

Lab 3.0 Fellow

UC San Diego Halıcıoğlu Data Science Institute · San Diego, CA

Taught Arduino and data science curricula to over 100 K-12 students, expanding STEM accessibility for underrepresented communities.
Engineered interactive robotics projects integrating servos and LEDs to translate complex data and hardware concepts into accessible art workshops.
Scaled program outreach by building a targeted database of 200+ school administrators, driving lab partnerships and increasing educational access across the county.

June 2025 – Aug. 2025

Research Intern, Product Management

LOZO · Shanghai, China

Led usability testing for an AI-powered speech analysis web platform across K-12 educators, students, and parents.
Synthesized qualitative user feedback into distinct personas and journey maps, identifying friction points and feature gaps.
Delivered actionable product recommendations that simplified the AI evaluation workflow for all user segments.

Projects

NCAA March Madness Cinderella Anomaly Detection Website →

Predicted tournament upsets to flag undervalued teams, using Logistic Regression, SMOTE, and PCA to boost F1 187%.
Ensured reliable scouting predictions by preventing data leakage through strict chronological testing and StratifiedGroupKFold cross-validation.
Deployed a serverless Vercel web app, enabling sports analysts to run real-time game predictions with zero latency.

Skills: Python, Pandas, Scikit-learn, SMOTE, PCA

League of Legends Position Prediction Website →

Built a Random Forest model predicting a player's position based on gameplay metrics with 77.3% accuracy.
Processed a 19k+ dataset through an ETL pipeline, using Matplotlib visualizations to refine model features.
Validated model fairness across player segments using statistical hypothesis testing to ensure unbiased predictions.

Skills: Python, Pandas, NumPy, Scikit-learn, Matplotlib

Twitter Student Sentiment Analysis

Analyzed 1.6M tweets using Pandas, detecting a 25% spike in negative community sentiment during finals week.
Validated models via SciPy statistical testing and built interactive Plotly dashboards to visualize actionable sentiment trends.

Skills: Python, Pandas, SciPy, Plotly

Skills & Technical Toolkit

Primary Focus Areas

Data Science & Machine Learning

Big Data & Cloud Analytics

AI & Developer Tools

Data Visualization

Languages & Tools

PythonSQLRJavaHTML/CSSJavaScriptGitGitHubJupyter Notebook

Data Science & ML

PyTorchPySparkDaskPandasNumPySciPyScikit-learnMatplotlibML Algorithms

Big Data, Cloud & AI

AWSApache SparkMapReduceLarge-scale Data ManagementMemory-Scalable AnalyticsGenAIGitHub CopilotVercelOracleDB