Leadership

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Nina Atkin is a seasoned leader of high impact data science and machine learning (ML)/artificial intelligence (AI) teams. Nina’s two decades of data science experience span financial services, healthcare, defense/law enforcement, and media and entertainment industries. Nina most recently launched and led the data science organization for a leading multinational mass media conglomerate, driving the gold standard for value-generating data science.

Nina enjoys developing well-rounded, business-minded data science organizations that lean into partnership, collaboration, and value-add results. She believes it is critical for data scientists to collaborate closely with the teams responsible for data, business outcomes, and tech execution to develop ML/AI solutions with measurable business impact.

Nina has an MS in Mathematics and Statistics from Georgetown University and a BS in Finance and Economics from University of Maryland.

Janie Scanlon, PhD, brings nearly twenty years of experience as a data science and AI leader. Most recently, Janie spearheaded a highly visible data science team at a leading streaming and entertainment company. There, she and her team leveraged cutting-edge Machine Learning (ML) to delve into customer preferences and viewing behaviors, informing critical business functions from targeted marketing to strategic content development. Prior to this role, Janie honed her expertise in research design, evaluation, and experimentation at prominent research institutes and think tanks within the education policy sector.

With this diverse background, Janie has developed a unique ability to bridge the gap between rigorous methodology and practical business application; she excels at translating complex data sets into clear, actionable strategies.

Janie earned her PhD in Quantitative Methods from the University of Pennsylvania and an MS in Statistics from Wharton.