Alejandro Fontal
Data Science · Bioinformatics · Scientific Software
Computational scientist working at the intersection of bioinformatics, epidemiology, and scientific software. I analyse complex biological and public health data, develop reproducible methods, and build tools that support research in practice.
Development Skills
Python
Expert (9+ years); primary language for package development, testing, and end-to-end analytical and ML work. Regularly use pandas, polars, statsmodels, scikit-learn, TensorFlow, PyTorch, plotnine, and FastAPI.
R
Proficient with tidyverse and Bioconductor, with strong R/Python interoperability in statistical and bioinformatics workflows.
Linux + HPC
Daily Linux user with scripting, remote systems, and HPC workflows using SLURM, Nextflow, and reproducible command-line pipelines.
Git + CI/CD
Collaborative development, code review, and automated testing and deployment with GitHub Actions and GitLab CI/CD.
Web + APIs
Development of lightweight web tools and REST services for research and data applications using HTML/CSS, JavaScript, and FastAPI.
Systems
Linux-based deployment for data and research applications, including containerized services, automation, secure remote access, and lightweight infrastructure.
Experience
5 roles visible
Postdoctoral Researcher · Data and Software Lead
Climate & Health Program @ ISGlobal
- Lead software and data engineering for the group, building internal packages, web tools, and GitHub-based workflows for reproducible research.
- Build reproducible pipelines for long-read aerobiome metagenomics and link results to health outcomes.
- Repurpose a laser-based pollen detector for bacterial discrimination using fluorescence, light scattering, and supervised machine learning.
PhD Fellow · Early-Stage Researcher
Climate & Health Program @ ISGlobal (HELICAL ITN)
- Developed time-series methods to quantify environmental signals in epidemics, including transient and lagged associations, multi-scale correlations, and phase-shift analyses.
- Integrated nationwide case data with climate reanalysis, remote sensing, GIS layers, and air-mass trajectories to study Kawasaki Disease, COVID-19, and influenza.
- Coordinated field sampling campaigns in Japan to characterize the biological and chemical composition of air masses.
Data Scientist
Protein Engineering @ DuPont Industrial Biosciences
- Integrated data-driven and machine-learning solutions into protein engineering workflows.
- Built and maintained reproducible bioinformatics and data pipelines.
- Partnered with wet-lab teams to design experiments and close the model-experiment loop, accelerating workflow automation.
Data Science Intern
DuPont Industrial Biosciences
Internship focused on machine learning for empirical protein design.
- Built, trained, and benchmarked deep learning models to predict enzyme performance from sequence and structure.
Assistant in MOOCs Development
Educational Staff Development @ Wageningen University
- Developed assignments and technical content for 10+ edX MOOCs.
- Provided technical support across course development workflows.
Education & Languages
PhD in Biotechnology
Universitat de Barcelona
- PhD focused on environmental determinants of disease onset, spatiotemporal modeling, and long-read aerobiome metagenomics.
MSc in Bioinformatics
Wageningen University & Research
- Data Science minor with cum laude distinction.
- Thesis on interpretable deep learning for protein subcellular location prediction.
BSc in Biotechnology
Universitat de Barcelona
- Thesis at the VHIR Bioinformatics Unit on meta-analysis of transcriptomics tools.