Hi! My name is Dan Schauder. I’m passionate about all things data, and I like to share my musings and discoveries in the world of data science, machine learning, and AI on this website.
I’ve always been intrigued with technology, but my path to data science has been somewhat unconventional. After graduating from the University of Richmond in 2011 with undergraduate degrees in Music (I play guitar, piano, and cello) and Business (focusing on Innovation & Entrepreneurship), I used the seed money I’d won in the UR Business Pitch Competition to develop and launch a webcasting platform to share live video streams of important events online (think weddings, memorial services, music performances, etc). I taught myself the web development essentials required to launch the service, and worked with several small businesses and individuals in the community to execute numerous successful webcasts.
A much younger me at a guitar performance in 2014
While I loved working in an entrepreneurial setting and learned a tremendous amount from the experience, I wanted to hone my ability to build consensus and effect meaningful change, so I spent about 3 years working in tech-focused sales roles in Philadelphia. In these roles, I managed relationships with tech leaders at small, medium, and enterprise institutions. In my conversations with CTO’s, CIO’s, and marketing leaders, I was struck by the sweeping changes taking place with respect to data. It was clear that advances in distributed computing and storage were enabling a revolution in the field of data science and analytics, that these changes would be transformational to the fabric of our society, and that I wanted to be a part of it.
Set on breaking into the world of data, I completed several MOOC’s focused on SQL, Python, and web development, opening the door to a position as a Business Intelligence Developer at a mortgage company called NewRez, LLC (known then as New Penn Financial) in June of 2013. I rapidly gained skill building dashboards with Tableau and grew into a leading technical contributor on the team. In addition to building dashboards and automating manual reporting processes, I built multiple custom web applications used throughout the 1,500-employee organization. I was recognized as Employee of the Month and promoted to Business Intelligence Manager in January of 2017.
In December of 2017, I was recruited to Cadent, LLC, an adtech firm focused on advanced TV analytics. Beginning as a BI Manager and advancing to the role of BI Director in November of 2019, I managed 12 direct reports. With my technical oversight and direction, my teams delivered over a dozen reporting and visualization initiatives in addition to key algorithmic contributions. I collaborated closely with the Data Science and Data Engineering teams, frequently producing the visualizations as the presentation layer for predictive forecasts.
The majority of my roughly 7-year career in Business Intelligence was devoted to web development, report automation, dashboarding, and descriptive analysis, but I’d had a longstanding desire to pursue predictive and prescriptive analytics. My work at Cadent stoked this desire as I came to appreciate the tremendous impact predictive models were having on the strategy of the business. I knew that an advanced degree in math and/or computer science would be important in securing a role focused on machine learning and advanced statistical modeling, and I was accepted into the top-ranked Master of Analytics program at Georgia Tech, beginning my studies in the Fall of 2020.
At the time of this writing (August of 2021), I am preparing to begin my final semester at Georgia Tech. I’ve learned more in the past year than I would have thought possible, with the rigorous curriculum covering an array of advanced modeling techniques. I created this site as a central repository for the exciting projects I’ve delivered during my stint in grad school to share with potential employers. Further, I plan to update this site periodically with my thoughts about general data science concepts, opinions on new developments in the state of the art, and educational resources for those working on their own data science journeys.
In my free time, I still love to play music, travel, hike, eat, and spend time with my lovely wife and dear dog (pictured here).
Me, my wife (MJ), and our dog (Toby) at the peak of Mount Moosilauke, NH in 2020
Thanks for stopping by, and if you find any of my posts interesting, offensive, exciting, amusing, or otherwise stimulating, I look forward to hearing from you! Feel free to leave a comment or reach out to me directly at danschauder@gmail.com