Applied Mathematician | MSc Computational Finance @ University of Padova
I work at the intersection of mathematics, artificial intelligence, and quantitative finance. My background combines rigorous mathematical training with hands-on experience building AI systems in the banking sector, and I'm now deepening my focus on computational finance in Italy.
MSc in Computational Finance — University of Padova, Italy (2026 – present)
B.Sc. in Applied Mathematics — Universidad del Valle de Guatemala Thesis: Quantum Walks Applied to Quantum Binomial Models for Option Pricing. The research explores how quantum walks, the quantum analogue of classical random walks, can be used to build binomial-type models for derivatives valuation, connecting quantum computing theory with financial mathematics.
Over the past two years, I've worked in the innovation area of a Guatemalan bank, building AI solutions and helping teams adopt them.
Autonomous AI agents
- Designed, built, and deployed AI agents for multiple business units, including internal audit, customer experience, legal document generation, financial advisory support, and digital channel monitoring
- Led the migration of agents from Microsoft Copilot Studio to Azure AI Foundry, and wrote the technical documentation and specifications for seven production agents
- Used Claude Code to accelerate development of internal tools and platforms
Financial data agent (RAG)
- Built a retrieval-augmented agent that answers questions about the Guatemalan banking system using public regulatory bulletins covering 19 banks
- Designed ingestion pipelines with Azure Document Intelligence and Azure AI Search, plus custom chunking that anchors every financial figure to its bank, indicator, and period to reduce hallucinations
- Pivoted from PDF extraction to a structured-data pipeline when dense financial tables proved unreliable, raising answer accuracy from 50% to 90% across three benchmark rounds
- Stack: Azure OpenAI (GPT-4.1, text-embedding-3-large), Azure Functions, Python, Node.js
Innovation, research & training
- Conducted market research to identify and evaluate innovation opportunities
- Designed and delivered AI fluency workshops and open innovation modules for the bank's internal innovation school
- Coordinated an internal AI agent-building competition (30 participants, 7 agents built)
- Coordinated an innovation observatory initiative in partnership with a university
| Project | Description |
|---|---|
| 🔬 Quantum Walks & Option Pricing | Thesis research applying quantum walks to binomial models for derivatives valuation |
| 🕸️ Twitter Network Analysis | Community detection (Louvain, Q ≈ 0.43), centrality analysis, and sentiment analysis on 5,596 tweets about traffic in Guatemala |
| 🧭 AI Search and Heuristics | BFS, DFS, Greedy Best-First and A* on 128×128 mazes; A* with Manhattan distance explores up to 95% fewer nodes than BFS |
| 📈 Guatemala Fuel Forecasting | Time series analysis and ARIMA forecasting of fuel data in Guatemala |
| ⚡ Spark ML Pipelines | Classification and regression pipelines with PySpark MLlib in a Dockerized environment |
| 🗄️ Spark Data Processing | Large-scale data processing with PySpark on Databricks |
Programming: Python · R · Java · Node.js · SQL AI & Agents: Azure AI Foundry · Azure OpenAI · Azure AI Search · Document Intelligence · RAG · Claude Code · Copilot Studio Data & ML: pandas · scikit-learn · NetworkX · NLTK · Spark · Databricks · Docker Quantitative Methods: Time Series Analysis · Statistical Modeling · Stochastic Methods · Option Pricing · Graph Theory
Spanish (native) · English · Italian (learning)
Computational Finance · Quantitative Risk · Quantum Computing · Autonomous Agents · Derivatives Pricing
Long term, I want to build a career in Europe and create bridges that help young Latin Americans access European academic and professional opportunities.
I'm always open to connecting with researchers, quants, and professionals in finance, AI, and applied mathematics, especially in Italy and across Europe.
