All students
Stephen Bracco Data Analytics track
Skills
- Python
- SQL
- ETL Workflows
- Git/GitHub
- AWS
- Tableau
- Excel
- Power Query
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Classification
- Clustering
- Data Cleaning & Wrangling
- Exploratory Data Analysis (EDA)
- SQL Joins
- Dashboard Design
- Regression Analysis
- GCP (BigQuery)
- Parquet
- REST/Socrata API
- pandas
- GeoPandas
- Matplotlib
- Seaborn
- Streamlit
- XGBoost
- Logistic Regression
- Random Forest
- scikit-learn
- Time-Series Validation
- Probability Calibration
- Risk Stratification
- SHAP
- SARIMAX
- Generative AI/LLMs
- A/B Testing
- AWS S3
Featured project
CabLink – MTA Bus Delay Prediction & Taxi Alert System
A team of four is building an ETL pipeline that processes 15.5M GTFS-Realtime vehicle positions from AWS S3 and integrates five data sources (20M+ rows) into a unified hourly panel to measure bus delays. The team benchmarked OLS, Ridge, LASSO, SARIMAX and XGBoost models under time-ordered validation, delivering a calibrated XGBoost classifier with ROC-AUC of 0.802. A rule-based alerting layer flags stop-level transit disruptions so taxi drivers can capture stranded passenger demand.
Resume
Download PDFBeyond the resume
Clubs and activities
- Machine Learning and Data Science club
- Financial Quants and Engineers club
Meet Stephen
Tell us who you are and what the role is. Darion Cole from TTPR will follow up by email and introduce you to Stephen.