My resume:
I enjoy exploring data I’m always learning something new Give me a problem… I will search a solution
Currently learning AWS and MLFlow.
I enrich the data gattering information from different sources, using tools like Python - Scrapy - Selium to automate the extraction of several multiple pages.
I develop, train and fine-tune supervised and unsupervised learning models with Scikit-learn and Keras, delivering accurate predictive solutions tailored to business needs.
I explore AI-powered business solutions by integrating the OpenAI API and building intelligent workflows using low-code tools like n8n. I enjoy prototyping agents that automate tasks, generate insights, and interact with data dynamically.
I'm currently learning AWS with a focus on data science workflows, exploring services like S3, EC2, Lambda, and SageMaker to build and deploy scalable machine learning pipelines.
💻 Programming
🧾 Version Control
🤖 Machine Learning
🖼️ Front-end
I’m a Data Scientist with a strong foundation in machine learning, currently expanding my skills in cloud development with AWS. I bring over 3 years of experience as a chemical engineer**.**
My transition into data science was fueled by curiosity and a deep interest in technology. I love building practical, AI-powered solutions that combine business understanding, clean code, and meaningful insights. Whether it's automating processes, predicting outcomes, or creating data pipelines, I enjoy tackling problems with a creative and analytical mindset.
Outside of projects, I’m always learning — from experimenting with OpenAI agents and low-code tools like n8n, to improving my deployment skills and collaborating on open-ended challenges. I thrive in collaborative environments, where sharing ideas and building together is part of the journey.