Description

Bioinformatician with 4 years of hands-on experience helping labs and companies move from raw data to discovery. If you are struggling with inefficient pipelines, messy data, or need a custom visualization to communicate your findings, I can help.

How I can help you:

I focus on the technical heavy lifting so you can focus on the biology. I develop clean, documented, and reproducible pipeline analyses for NGS, RNA-seq, or variant calling. When existing tools fall short, I develop custom bioinformatics software to fit your specific research questions.

What makes me stand out:

I believe data is only useful if you can understand it. That’s why I put a strong emphasis on exploratory data analysis and visualization. I don't just give you numbers; I provide the context and visuals that reveal the story hidden in your data.

Recent projects have included:

- Building scalable analysis pipelines for high-throughput sequencing facilities.

- Creating interactive dashboards using PowerBI.

Let's connect to discuss how I can turn your data into your next breakthrough.

Industry field of expertise

Languages

English
Native or bilingual
Spanish
Native or bilingual

Workplace preferences

Can work on-site

Sevilla (up to 50km)

CICbioGune
Data analyst - Bioinformatician
RESEARCH
March 2023 - January 2026 (2 years and 10 months)
Bilbao, Spain
Cancer Cell Signaling and Metabolism Lab

- Developed and mantained data analysis pipelines, with a focus on bulk RNA-seq.
- Process and analysis large-scale datasets from public genomic databases (TCGA, GEO).
- Applied ML models to extract insights from complex data (K means, FCM).
- Used Git for version control to ensure reproducibility and facilitate collaborative development.
- Communicated findings through data visualizations, interactive dashboards, and technical reports to support cross-functional decision-making.
Data Visualization Exploratory Data Analysis ETL Git Machine learning
UOC & Hospital Bellvitge
Undergraduate Researcher
February 2022 - June 2022 (4 months)
Developed automation tools to reducing manual effort in data extraction, reducing the effort from weeks to minutes.
Processed and cleaned large clinical datasets, ensuring accuracy and consistency for analysis.
Applied biostatistical and machine learning techniques (Logistic regression) to identify trends and correlations in vitamin D.
UGR - Ecology Department
Undergraduate Researcher
January 2018 - July 2019 (1 year and 6 months)
Conducted descriptive and inferencial statistical analysis to study macroinvertabrate communities.
Assessed environmental factors affecting species distribution and ecosystem variation.