🚀 Senior Member of Technical Staff with a focus on analytics and machine learning
🏫 Currently studying Computational Data Analytics at Georgia Tech
📍 Based in Texas
📧 Email: sega97@gmail.com
🔗 LinkedIn
👨‍💻 GitHub: SantiagoEnriqueGA

Blending deep experience in data analytics, machine learning, and software engineering, I transform data into actionable insights and innovative solutions.

• Senior Member of Technical Staff - AT&T, Dallas, Texas (Present)
• Broadband Advanced Analyst - AT&T, Dallas, Texas
• Metrics Reporting Analyst - AT&T, Dallas, Texas
• Data Implementation Analyst - IHS Markit, Dallas, Texas
• Software Developer - ServiceNow - Sabre Corporation, Southlake, Texas

• Languages: Python, R, SQL, C, Java, JavaScript
• Libraries: Pandas, NumPy, Scikit-learn, Keras, PyTorch, PySpark
• Analytical Tools: Power BI, Tableau, Palantir
• Certifications: Advanced Data Science IBM Specialization, Advanced Machine Learning and Signal Processing, Applied AI with DeepLearning, Fundamentals of Scalable Data Science

• Master of Science in Analytics (Computational Data Analytics Track) - Georgia Institute of Technology (Expected 2024)
• Bachelor of Science in Information Technology and Systems - The University of Texas at Dallas (2020)

• Rental Pricing Dashboard - ISYE 6414 Regression Analysis

  • Developed an XGBoost model for predicting apartment rental prices with a MAE of 47.90.
  • Led data collection, aggregation, and model fine-tuning for optimal accuracy and robustness.

• Conway's Game of Life - Personal Project

  • Implemented Conway's Game of Life using Pygame for graphics and Numpy for array operations.
  • Developed multiple versions with enhancements such as optimized drawing, pause/resume functionality, and user interaction improvements.
  • Created various screens for user settings and controls, including start menu, wrap options, glider configurations, and game world size settings.
  • GitHub Repository

• Semantic Artist Similarity Analysis - Personal Project

  • Analyzed artist similarity using the Semantic Artist Similarity (SAS) Dataset.
  • Implemented Python scripts (SAS_networkx.py) for building and analyzing artist similarity networks using NetworkX and visualizing them with Plotly.
  • Created an HTML file (SAS_D3.html) for interactive visualization of the network using D3.js.
  • Explored functionalities such as parsing data, network metrics calculation, furthest connectivity analysis, and shortest paths.
  • GitHub Repository

• Used Car Data Scraping and Analysis - Personal Project

  • Created class for automatically scraping data from Cars.com using BeautifulSoup.
  • Created pipeline to scrape data on several vehicle models, clean and analize the data.
  • GitHub Repository

• Custom Clustering - Personal Project

  • Created classes for KMeans and DBSCAN from scratch using only numpy for array processing.
  • Custom classes allow for use of multiple clutering evaluation measures: elbow method, Silhouette Score, Davies-Bouldin Index, Calinski-Harabasz Index.
  • Done in order to understand the workings of clustering algorithms, and how to fit them to specifit datasets by building them from scratch.
  • GitHub Repository

• Custom Ensemble Learning - Personal Project

  • Created class for creating random forest classifiers and regressors, and class for gradient boosted decision tree classifiers, regressors.
  • Created in base python using only numpy for speedy array processing.
  • Done in order to understand the workings of ensemble learning algorithms, and how to fit them to specifit datasets by building them from scratch.
  • GitHub Repository

• Dallas CASA (Court Appointed Special Advocates) (2021 - Current)
• Co-Recruitment Chair, Delta Tau Delta Fraternity, UT Dallas (2016 - 2020)