As a Data Scientist with extensive experience at CBRE, my academic background in physics and more than eight years in data science and analytics equip me to address complex challenges in the nearly any domain. A standout achievement is my pioneering rent prediction model, which leverages cutting-edge insights to deliver substantial cost savings for our clients, directly enhancing customer value. Further exemplifying my innovative approach is the development of an optimization engine for occupancy managers, which has transformed their planning strategies by significantly cutting down the required time for efficient space management.My commitment to applying scientific expertise to solve practical problems shines through my involvement in various significant projects. I have played key roles in creating simulations for NASA's decadal survey, employing sophisticated methods to clean satellite data, and conducting analyses to pinpoint underperforming units within a restaurant holding company.At the core of my professional philosophy is a strong belief in creating solutions that primarily enhance, and never inhibit the workflow of clients. I thrive on interactions with fellow data scientists and experts across different sectors, fostering a multidisciplinary approach to problem-solving. For a closer look at my previous endeavors and current pursuits, please feel free to visit my GitHub page at https://www.github.com/mandomal or my personal website at https://www.mando.blog.