Dynamic and results-driven Data and Machine Learning Engineer with extensive experience across data science, analytics, and automation. Currently, as the Automation & Analytics Manager at Uber LatAm, I lead projects that optimize operational efficiencies and enhance data-driven decision-making. By developing automation processes that save the team up to 18 hours per week and building dashboards to track communication performance across LatAm, I transform raw data into actionable insights that drive business growth and improve engagement metrics.
At Vixtra, I honed my skills in cloud infrastructure and time-series forecasting, leveraging over 20 years of data to develop a machine learning model that improved forecast accuracy by 50%. I created and benchmarked BI reporting using tools like Looker, Tableau, and Power BI, setting up the company’s first reporting processes and using AWS services like Redshift and Lambda to streamline data ingestion and implement CI/CD pipelines. My experience with Python, SQL, and scalable architecture allowed me to craft data solutions that integrate seamlessly across platforms, increasing productivity and reducing maintenance.
With a background in deep learning and computer vision, I began my career as a Junior Data Scientist, researching and implementing a custom OCR solution using TensorFlow, which reduced reliance on third-party software and cut costs by 20%. My academic foundation, including an MSc in Electrical and Computer Engineering, enables me to excel in research-driven projects and apply best practices in software development, such as Test-Driven Development (TDD) and continuous integration, to build robust, scalable machine learning solutions. I am passionate about applying data science and engineering to real-world business problems, delivering impactful insights through rigorous research and technical innovation.