Hey there! I'm Geovanny

Software/Data engineer with +4 years of experience developing data-driven software. Specialized in building secure, efficient, and reliable systems for transforming and storing healthcare data.

Experience

•

Big Data Engineer

Teladoc Health

Apr 2023 - Present

Built a cloud native Big Data Analytics pipeline able to process up to 10 million records a day.

Lead Infrastructure as Code (IaC) efforts of the team.
Build ETL pipelines to ingest electronic health records (EHR) data from multiple sources, transform and store it in a structured format. Processing up to 10 million records a day.
Provision multi-environment Azure Databricks and Apache Airflow resources.
Design and implement an automated testing and deployment strategy (CI/CD).

•

Software Engineer

Made Of Genes

Sep 2020 - Apr 2023

Collaborated on multidisciplinary tasks within bioinformatics and IT teams of the company.

Genetic and biochemical data integration through ETL pipelines developed with Python.
REST APIs (with Flask and NodeJS) development to support data integration workflows.
Data modelling for SQL and NoSQL.
Full stack web development with MEAN stack.
Infrastructure as Code management with AWS, Terraform, Kubernetes and Kafka.
Unit, integrity and end-to-end tests (Jest and Pytest).

•

Research Student

Barcelona Supercomputing Center

Jan 2021 - May 2021

Developed my final thesis titled “Machine Learning to predict protein function based on co-evolutionary information”, awarded with "with Honours" mention for both Computer Science and Biotechnology degree.

Education

•

MSc in Data Science

Universitat Oberta de Catalunya

Sep 2021 - Jun 2023

Master's Degree in Data Science, with a focus on Machine Learning, Deep Learning, and Big Data.

•

Dual BSc in Computer Science and Biotechnology

Universitat Rovira i Virgili

Sep 2016 - Jun 2021

Bachelor's Degree in Computer Science and Biotechnology. Completed full credits in both degrees (400 ECTS). Developed a solid background in software development, bioinformatics, and the intersection of both fields.

Projects

ML in ARGs - Machine Learning to fight against Antibiotic Resistant Genes

Python
R
Pandas
Scikit-learn

Using genetic information from resistant bacteria, it is possible to model the characteristics that confer resistance to certain antibiotics. This information could be used to predict new potential resistant genes or sets of genes and take appropriate action. In this project, real data from a series of resistant bacteria identified in the laboratory will be used to build a machine learning model capable of predicting potential resistance genes (ARGS).

Glaucoma Detection - CNN model to detect glaucoma disease using fundus images

Python
TensorFlow
Pandas
Matplotlib

In this project, we developed a convolutional neural network (CNN) based on the Xception architecture to classify fundus images for glaucoma detection, achieving an F1-score of 0.87 ± 0.05. While provided training folds were used, a more flexible cross-validation strategy would be preferable to enhance model evaluation. Key factors in designing partitions include ensuring diversity and balanced class distribution to improve generalization.

PP2GO - Phylogenetic Profiling To Gene Ontology

Python
Pandas
Scikit-learn
Matplotlib

Machine Learning to predict functional relationships of uncharacterized proteins through orthology and co-evolution information. A pipeline was developed to test different models and filters in a High-Performance Computing environment. Among the six supervised classification algorithms evaluated, Random Forest method provided the most accurate predictions, with a mean F1-score of 0.61.

About me

This is Geo! My curiosity to better understand the world around me has led me to study science and technology. Now, I am grateful that I have turned my passion into a career.

I help enterprises build data-driven solutions that improve their daily operations. My main focus has been building software that ensures data is transferred and stored securely, efficiently, and reliably. Along the way, I have developed a strong passion for the DevOps culture. I believe its principles are essential for creating robust and scalable systems, especially in this era of cloud computing.

However, my interests go beyond the technical aspects of software development. I am especially interested in how Artificial Intelligence can be applied to solve medical and health problems. The intersection of biology and technology is a field that I believe will have a profound impact on the future.

Outside work, you will find me practicing all kinds of sports, like running, climbing or tennis. I also love reading about science, particularly about the mistery of physics and the universe. Of course, as a curiosity-driven person, I enjoy traveling and discovering new places and cultures.