• Developed and implemented a minimum viable product (MVP) of a recommender system, utilizing three machine learning models to achieve a 12% boost in phosphoric acid production. • Completed an end-to-end Proof of Concept (PoC) for an industrial data science project aimed at reducing methanol production costs.

• Extended continuous operation period of a flame reactor by 30% by creating a machine learning model to anticipate clogging using time-series data from sensors • Sped up the procurement documentation classification process by 81% by developing a Streamlit- based Python web application using TF-IDF and classic machine learning algorithms

Wrote technical documentation, drew process diagrams for a team of data scientists which helped in the successful implementation of the project for the early detection of anomalies in the operation of granulation equipment

• Led a project to deploy and bring to work a system of electronic documents, based on Documentum, with 1300 core users • Implemented software to edit documents automatically which reduce the time of the editing process by 67%

• Developed applied software to automate manufacturing and office processes in C# • Worked with MS SQL and MySQL databases to implement their data into applications • Created web applications in PHP, ASP.NET/C#