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I am Jeison,

I am a Software Engineer with 7+ years of diverse experience in various tech domains and business objectives. I embrace team working, continuous learning, and good development practices. My current goal is to transform machine learning models into real-world solutions that create value and impact.

In my latest role, I was part of the Machine Learning Delivery team at Mercado Libre, the leading e-commerce platform in Latin America. I orchestrate data wrangling with SQL queries on BigQuery, fueling the cutting-edge ML models that drive user engagement with Mercado Pago. I collaborate with a marketing-focused team, leveraging data-driven insights to design and deliver personalized push notifications and email campaigns, tracking and elevating KPIs like open rate, conversion rate, and lift.

Previously, I worked on Backend Development mastering Python and frameworks like Django and Flask. I have also experience with JavaScript and Elixir (Phoenix). I contributed to the development of the 'EY Blockchain Analyzer: Reconciler' at Globant, with Ernst & Young as a stakeholder, where I became proficient in agile methodologies and ventured into the Microsoft Azure ecosystem, using Docker and Kubernetes for service deployment.


Jeison Pacateque's Projects

asphalt-mixtures-aging-simulator icon asphalt-mixtures-aging-simulator

This project performs a 3D reconstruction of a cylindrical asphalt mixture sample from a set images on a Dicom file format. The components of asphalt mixture will be identified through 3-phase segmentation. Additionally, a 3D model of the asphalt mixture reconstruction was developed. The project was implemented on the Python programming language using the open-source libraries Numpy, Scipy, Pydicom, Scikit-learn, Matplotlib and Mayavi. A simulation of the asphalt mixtures aging process is implemented using numerical methods on the mechanical, themical and chemical fields.

python-mlops-cookbook icon python-mlops-cookbook

This is an example of a Containerized Flask Application that can deploy to many target environments including: AWS, GCP and Azure.

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