Open to opportunities

Aldo Galeano

@aldogaleano

Data Scientist and Machine Learning researcher using Python, transformers, and LLMs to model biological data and predict missing associations.

Paraguay

Message

What I'm looking for

I’m looking for a data science role where I can build and deploy ML/LLM and transformer models on biological datasets, collaborate with research teams, and use cloud + GPU infrastructure to drive model performance and publish impactful results.

I’m a Data Scientist and Machine Learning researcher who builds end-to-end analytical pipelines—preprocessing, ingestion, modeling, and evaluation—for structured and unstructured datasets using Python, SQL, and Jupyter-based workflows.

In my current role at Paccanaro Lab, I develop machine learning models for representation learning, pattern discovery, and prediction from association data. I’ve trained transformer-based generative models for protein sequence generation and applied LLM and transformer techniques for protein classification, feature extraction, and downstream analysis.

I work comfortably with large-scale biological and protein datasets and the practical infrastructure required to scale deep learning—using cloud-based environments plus GPU/VM setups to train and optimize models. I also collaborate with cross-functional research teams and contribute to peer-reviewed publications, presenting insights in written and oral formats.

Before that, as a Data Science Technician at CITIC, I performed data preprocessing, cleaning, and integration of biological networks with FDA-approved drug features to support predictive modeling. I implemented and evaluated mathematical models based on graph kernels for similarity assessment and prediction tasks, and I’m continuing this research direction through my PhD in Applied Mathematics and Data Science.

Experience

Work history, roles, and key accomplishments

Current

Researcher (Data Science)

Current

Paccanaro Lab

Jan 2021 - Present (5 years 4 months)

Designed and implemented end-to-end data science pipelines for structured and unstructured datasets, covering preprocessing, ingestion, modeling, and evaluation using Python, SQL, and Jupyter workflows. Developed transformer-based protein sequence generation and applied LLM/transformer techniques for protein classification and downstream analysis, supporting GPU/cloud training and collaborating on

Python SQL Jupyter Data Pipelines Deep Learning Transformers Representation Learning LLM

Data Science Technician

Centro De Investigacion Citic

Jan 2020 - Jan 2021 (1 year)

Performed data preprocessing, cleaning, and integration of biological networks with FDA-approved drug features to support predictive modeling. Implemented and evaluated graph-kernel-based mathematical models for similarity assessment and prediction tasks.

data preprocessing Data Integration predictive modeling

Education

Degrees, certifications, and relevant coursework

Escola de Matematica Aplicada – Fundação Getulio Vargas

Doctor of Philosophy, Applied Mathematics and Data Science

2021 - 2025

Activities and societies: Final Degree Project: Learning Object Representations to Predict and Explain Missing Associations. Advisor: Prof. Alberto Paccanaro.

Pursuing a PhD in Applied Mathematics and Data Science with research in data analysis, machine learning, deep learning, and representation learning from large-scale association data. Applied LLMs and transformer architectures for protein sequence modeling and biological datasets, including a final project on learning object representations to predict and explain missing associations.

Facultad de Ingenieria, Universidad Nacional de Asunción

Mechatronic Engineer, Mechatronics Engineering

2013 - 2020

Activities and societies: Final Degree Project: Frictionless Platform for Nanosatellite Attitude Determination and Control System Testing. Advisors: Dr. Diego Stalder, Dr. Diego Kurita.

Completed a Mechatronic Engineering degree focused on system modeling, control systems, microcontroller programming, and numerical computing using C++, MATLAB, and Python. Completed a final degree project on designing and implementing a frictionless platform for nanosatellite attitude determination and control system testing.