Nicolaus Schmandt

Nicolaus Schmandt is a highly skilled Data Scientist with a strong background in product management and programming. He has a proven track record of successfully delivering results in corporate settings.

His experience includes overseeing stakeholder relations and product planning for data science algorithms, resulting in significant revenue and cost savings for companies. Nicolaus has expertise in coding, communicating, and overseeing the production of various machine learning algorithms, leading to projected revenue enhancements in the retail sector.

He is adept at communicating analytic results to executives, with a focus on customer and inventory segmentation. Nicolaus has a wealth of experience in grant writing and deep learning, image processing, stochastic modeling, and biomedical research, with multiple publications in high-impact peer-reviewed journals.

His educational background includes a PhD in Neuroscience from Case Western Reserve University, a Bachelor's Degree in Physics, Mathematics, and Music from Amherst College, and an MBA from NYU Stern School of Business. He has also completed a Research Fellowship in Bioengineering and Biomedical Engineering at the University of Chicago.

Nicolaus has held key positions in reputable organizations such as Humana, where he served as a Lead Data Scientist, and Wayfair, where he was a Technical Data Science Program Manager. He has also worked at Tailored Brands, Inc., Insight Data Science, Kershner Trading Group, University of Chicago Medicine, and other esteemed institutions. His diverse experience includes roles such as Deep Learning Scientist, Data Scientist, Biomedical Scientist, and more.

With a unique blend of technical, scientific, and business literacy, Nicolaus Schmandt excels in tactical planning, analysis, and data science. His wide-ranging skill set and expertise make him a valuable asset in the field of data science and product management.