📍 New York, NY 10001

• LinkedIn @santiagogsv

I'm an adaptable Data Analyst fluent in English, Spanish, and Italian, with a robust background in economics. Based in New York City, I specialize in Python and Rust for data analysis and networking, leveraging modern technologies to improve web performance and data processing. My toolkit includes extensive use of Python for data-driven insights and Rust for high-performance networking, with a keen interest in Cloudflare's innovative use of Rust to enhance web infrastructure.

• Python Libraries:
  • Polars & Numpy: Utilize for data manipulation and numerical analysis to clean and prepare large datasets.
  • Matplotlib & Statsmodels: Employ for data visualization and statistical modeling to uncover trends and patterns.
• Machine Learning with Python:
  • Scikit-learn: Implement machine learning algorithms for predictive modeling.
  • PyTorch: Use for building and training advanced neural network models.
• Data Management:
  • SQL: Manage databases efficiently.
  • Excel: Utilize for additional data processing and visualization.

• Rust Libraries:
  • Axum: Leverage for creating high-performance web applications and APIs with ease.
  • Tokio: Use for asynchronous programming to handle multithreaded network operations efficiently.
  • WASM (WebAssembly): Explore for compiling Rust to WASM, enabling high-performance, low-level operations in web environments.
  • Pingora: Interested in using as a high-throughput HTTP proxy to optimize network requests, inspired by Cloudflare's use of Rust in their infrastructure.
  • Cloudflare Libraries: Specifically, the cloudflare-rs library for interacting with Cloudflare's APIs to manage Cloudflare Workers and other services.
• Rust in Data and ML:
  • Polars: Use for data processing in Rust, similar to how it's used in Python, for fast data manipulation.
  • Burn: Experiment with this Rust library for machine learning, aiming to bring Python's ML capabilities into Rust's performance ecosystem.

• TypeScript:
  • Employ for type-safe frontend development, enhancing scalability and maintainability of web applications.
  • Integrate with React or Qwik for dynamic, data-driven UIs.

Bachelor of Science in Economics | UNAM (2018 - 2023)

• Applied advanced statistical techniques and Python programming to model and analyze economic data.

• Data Analysis with Rust: Experimenting with Rust for performance-critical data analysis tasks, focusing on speed and safety.
• Network Optimization using Rust: Developing projects to showcase the use of Rust in network programming for lower latency and better resource management.
• Cloudflare Workers Projects: Building serverless applications with Cloudflare Workers written in Rust for edge computing scenarios.

• Continuously learning about new developments in Rust for system programming and network optimization.
• Exploring the intersection of AI, data analysis, and network performance using modern programming paradigms, especially the synergy between Rust and Python for ML tasks.