Hi, I'm
Systems & Computing Engineer · M.Sc. Candidate
I turn complex challenges into scalable, dependable engineering solutions by bringing together software, data, and AI. Currently at Scotiabank, contributing to technology for banking at scale.
I design and build engineering solutions for complex, real-world problems, connecting software, data, and AI with the needs of the people and organizations that use them. My experience spans banking at Scotiabank, healthcare at Nebula Medical, and enterprise technology at Caseware. I am pursuing an M.Sc. in Systems and Computing Engineering at Universidad de los Andes, where I deepen my understanding of how complex systems are designed, analyzed, and improved.
My systems and industrial engineering background helps me connect architecture decisions to operational constraints. I focus on how software behaves as workloads grow: latency, throughput, failure recovery, observability and cost. My goal is to build systems that teams can understand, operate and evolve, as well as deploy.
Systems for banking, healthcare and audit. From integration to production.
February 2026 - Present
Develop backend services and integrations for banking technology teams, supporting financial operations with reliable and maintainable software in a regulated enterprise environment.
Universidad de los Andes
Universidad de los Andes
Universidad de los Andes
Open-source contributions, independent tools and applied research.
Open-source contribution
Local search across GitHub, Notion, Slack and files, with a vector index and an MCP server for AI agents.
Applied machine learning
A talent matching platform combining document understanding, skill graphs and candidate matching with explainable LLM scoring.
Developer tooling
A modular Python library that turns structured career information into DOCX and PDF résumés.
Predictive modeling
An ML pipeline for temporal features, calibrated ensemble predictions and Kelly Criterion stake sizing.
Event-driven backend
A real-time financial alert service with WebSockets, Redis messaging and PostgreSQL persistence.
Undergraduate research
Machine learning for biological data using PCA, class balancing and neural networks in TensorFlow and Keras.
Optimization
Multi-objective scheduling in Java and C++ to balance charging costs and customer service levels.
Full-stack application
A Django application for facility administration, records management and resource allocation.
Distributed systems
Spring Cloud services with RabbitMQ messaging, JWT authentication, resilience patterns and distributed tracing.
Research assistant at Universidad de los Andes - Colombia in Bogotá, Distrito Capital, Colombia. Researching large-scale urban traffic networks across Latin American cities, continuously collecting traffic data in real time. Built the end-to-end Python data pipeline, from automated data collection and Parquet storage to network analysis, regression modeling, and R²-based evaluation. Deployed and automated the research infrastructure on Linux servers using Python, Parquet, YAML-based configuration, and reproducible command-line workflows, generating datasets, models, and analyses.
Engineered deep learning architectures for high-dimensional biological data. Leveraged PCA for dimensionality reduction and Keras/TensorFlow for model development, achieving 98% accuracy in complex pattern recognition.
Read PublicationShowcased undergraduate thesis findings at the 2025 Analytics Forum, presenting advanced machine learning applications in bioinformatics to an audience of industry experts and researchers.
Speaker at the Center for Optimization and Applied Probability (COPA) to discuss the integration of neural networks and probabilistic modeling in biological systems.
I connect software, data, AI, and cloud technologies to turn complex requirements into solutions that work in the real world.
01
Clarify the real need, constraints, users, and how each part affects the whole.
02
Bring together software, data, AI, and infrastructure where they create practical value.
03
Prioritize performance, reliability, security, and the ability to evolve over time.