Masoud Masoumi

Welcome to my corner of the digital space! I’m Masoud Masoumi, a passionate problem solver with a strong academic foundation in Mechanical Engineering. My journey extends beyond traditional engineering, delving into the realm of data science and machine learning. My expertise lies in harnessing cutting-edge technologies to address complex challenges. Beyond the classroom, I’ve immersed myself in research, exploring applications of machine learning and data analytics in science and engineering.

In addition to my academic pursuits, I’ve earned certificates in Applied Mathematics-Data Analytics and completed specialized training in Deep Learning. My professional trajectory spans a spectrum of projects, ranging from predicting stress fields using Convolutional Neural Networks to designing electricity consumption models with real-time energy data. I’ve also delved into data analytics and machine learning solutions for atmospheric data analysis and predictions.

Since leaving my full-time academic position, I worked as a Physical Scientist at the Hydrographic Surveys Division within the Office of Coast Survey, part of NOAA’s National Ocean Service. In this role, I was primarily responsible for all phases of automated workflow development for the National Bathymetric Source model, including design, algorithm and software development, testing, and documentation.

Recently, I joined the Internal Revenue Service as a Data Scientist, where I will focus on exploring novel data retrieval methods and providing innovative recommendations for data-driven decisions. Additionally, I will be collaborating with business and technology partners to understand their needs and implement analytical solutions. My responsibilities will also include cleaning, transforming, analyzing, and integrating structured and unstructured data from various sources, as well as troubleshooting and proposing solutions to project bottlenecks.