Quantitative researcher who builds the data infrastructure to answer the questions.
I'm an Economist (PUCP, 2024) who works across the full data lifecycle — from defining the right question and choosing the right methodology, to building the pipelines and models that produce the answer.
My background in statistics and econometrics gives me a rigorous foundation for empirical research and causal analysis. My experience in data engineering means I can design and automate the infrastructure that makes that research possible. And my growing work in machine learning and AI engineering lets me apply modern techniques to real-world problems — not just as tools, but with an understanding of when and why they're appropriate.
At CENTRUM PUCP I design relational databases, build end-to-end ETL processes in Python, and develop AI-powered tools for institutional workflows. Previously as Marketing Director at Revista Económica PUCP, I combined data analysis and visualization to drive editorial decisions.
- 🏆 Finalist at Datatón OEFA 2025 — predictive model for dengue outbreak detection using environmental data
- 📚 Enrolled in AI Engineer and Multicloud Data Engineer specialization programs
- 🔭 Currently expanding my portfolio with ML pipelines, RAG systems, and economic forecasting models
- 🌎 Based in Lima, Perú — open to data science, analytics, and data/AI engineering roles
Bibliometric analytics pipeline with a live interactive dashboard
- Designed a modular ETL pipeline using Medallion Architecture (Bronze / Silver / Gold) orchestrated with Apache Airflow on Docker
- Ingests data from the OpenAlex API and surfaces it through a Streamlit dashboard with dynamic filters by field, year, and institution
- Stack: Python · Pandas · Plotly · Airflow · Docker · Streamlit
Real-time crypto market tracker with interactive visualizations
- Built a real-time ETL system that fetches and processes cryptocurrency data from the CoinGecko API
- Features a treemap of market cap, 7-day trend charts, and a dynamic theming system
- Stack: Python · Streamlit · Plotly
Exploratory analysis of rare earth trade flows (1995–2022)
- Analyzed global rare earth trade data from OEC, mapping top exporters, importers, and trade balances by country
- Built an interactive Power BI dashboard published to Power BI Service, with data cleaning and transformation in R
- Stack: R · Power BI · DAX
| Project | Description | Status |
|---|---|---|
| 🤖 End-to-end ML pipeline | MLflow + FastAPI deployed model | 🔨 In progress |
| 📚 RAG pipeline | LangChain + ChromaDB document QA | 🔨 In progress |
| 📊 Customer segmentation | Churn model + RFM segmentation | 🗂️ Planned |
| 📉 Economic forecasting | Time-series with Peruvian public data | 🗂️ Planned |
Open to data science, analytics engineering, and AI roles in Lima, Perú.
LinkedIn ·
Portfolio ·
Email