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Pablo Torreira Pardo

@pablotorreirapardo

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Junior Data Scientist and computational biologist focused on bioinformatics ML and data-intensive backend.

Spain

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What I'm looking for

I’m looking for a role where I can apply Python-based ML to bioinformatics and medical data, while growing my backend software development skills for data-intensive scientific applications and reliable model deployment.

I’m a Junior Data Scientist / Computational Biologist who enjoys translating complex biological data into reliable, actionable insights using programming and machine learning. I combine biological data analysis with strong coding foundations to build data-intensive scientific applications.

In my “Cátedra Inditex-UDC in Artificial Intelligence for Green Algorithms” experience, I trained Machine Learning models to predict nanomaterial toxicity using Python and scikit-learn. I also focus on model rigor by working through the full train/validation/test mindset used in practice.

As a Data Analyst Intern, I developed a web application for interactive visualization of streaming mammary tissue classifier data with Python and Plotly. I worked on medical image segmentation and classification, and I handled data transformation and integration with Python, SQL, SQLAlchemy, Pandas, NumPy, and relational databases (MySQL/MariaDB).

In my bioinformatics internships and projects, I analyzed filtered SNP genomic panels from Illumina sequencing data and built an automated Python pipeline for segmenting corneal layers in AS-OCT images. I’ve also used HPC-oriented scripting (Bash) and libraries like PySpark, OpenCV, and Biopython to tackle real-world bioinformatics challenges.

Experience

Work history, roles, and key accomplishments

Junior Data Scientist

Cátedra Inditex-UDC

Oct 2025 - Mar 2026 (5 months)

Trained machine learning models to predict nanomaterial toxicity using Python and scikit-learn. Applied data analysis workflows for biological/material datasets.

Python scikit learn Machine Learning Model Training Toxicity Prediction Data Analysis data preprocessing NumPy

Data Analyst Intern

Néboda Farms

Jun 2025 - Oct 2025 (4 months)

Developed a web application for interactive visualization of streaming mammary tissue classifier data using Python and Plotly. Transformed and integrated datasets with Python, SQL, and SQLAlchemy, and practiced machine learning for classification using Random Forest and SVM.

Python Plotly Web Application Development SQL SQLAlchemy Pandas Random Forest SVM MySQL MariaDB

Bioinformatician Intern

Grupo Acuigen

Feb 2024 - Apr 2024 (2 months)

Obtained and analyzed filtered SNP genomic panels from Illumina sequencing data using R, Python, and Galaxy. Built an automated Python pipeline with HPC scripting (Bash/Perl) to segment corneal layers in AS-OCT images and generate quantitative graphical reports.

R Python Galaxy BASH Perl AS OCT Image Analysis SNP Analysis Sequence Alignment (Biopython)

Education

Degrees, certifications, and relevant coursework

CIFP Rodolfo Ucha Piñeiro

Software Development

2025 -

Ongoing training at CIFP Rodolfo Ucha Piñeiro (since September 2025), covering object-oriented programming, web technologies, systems administration, and database administration.

University of A Coruña (UDC)

MSc, Bioinformatics for Health Sciences

2024 - 2026

MSc in Bioinformatics for Health Sciences at the University of A Coruña (UDC) from September 2024 to July 2026. Coursework includes biological data analysis and machine learning/computer vision using Python and related tooling.

University of A Coruña (UDC)

BSc, Biology

2019 - 2024

BSc in Biology at the University of A Coruña (UDC) from September 2019 to February 2024. Includes biological data analysis and programming for data-intensive scientific applications.