You can download my complete CV as a PDF using the download button at the top-right of this page.
Quick Summary¶
PhD candidate in atmospheric sciences specializing in:
Big data processing and data engineering for Earth observation
Machine learning applications for weather and climate
Cloud-native data formats (Zarr, Parquet) and ARCO principles
Open science and FAIR data practices
Work Experience¶
Data Science Intern | Earthmover PBC | May–August 2025
Developed analysis-ready, cloud-optimized (ARCO) datasets for meteorological data products
Focused on improving radar data accessibility and usability
Created educational content and documentation for ARCO best practices
Radar Meteorologist & Software Developer | IDEAM (Colombian National Weather Service) | 2016–2020
Developed radar and satellite data visualization tools for operational meteorologists
Designed multi-sensor quantitative precipitation estimation products
Integrated weather data pipelines for national early warning systems
Provided radar meteorology training to aviation and weather personnel
Education¶
Ph.D. in Atmospheric Sciences | University of Illinois at Urbana-Champaign | 2020–2025 (Expected)
M.Sc. in Meteorology | Universidad Nacional de Colombia | 2018
B.Sc. in Agricultural Engineering | Universidad Nacional de Colombia | 2013
Skills¶
Programming & Tools: Python, Shell, Git, Docker | Conda, Mamba, Pip, UV
Data Science: Pandas, Xarray, SQL, VirtualiZarr, Kerchunk | PyTorch, TensorFlow, Scikit-learn
Workflows: HPC (Dask, Slurm) | Data versioning (Icechunk) | CI/CD (GitHub Actions, pre-commit) | Cloud (AWS S3, Coiled)
Data Formats: Zarr, NetCDF, HDF5, GRIB, Parquet | ARCO principles
Software Projects: raw2zarr (Lead Developer) | xarray and xradar (Contributor) | Open Radar, Project Pythia (Member)
For complete details including publications and talks, please download the full CV above.