Dan Frank
About Dan Frank
Dan Frank is a Staff Data Scientist at Watershed, where he has worked since 2022. He has extensive experience in data science, having held positions at various companies including Coinbase, Airbnb, and Facebook, and holds advanced degrees in Computational Mathematics and Applied Mathematics from Stanford University and UC Berkeley.
Work at Watershed
Dan Frank has been serving as a Staff Data Scientist at Watershed since 2022. In this role, he focuses on leveraging data science techniques to support the company's mission. His work involves applying his expertise in experimentation, causal inference, and machine learning to develop data-driven solutions. Based in the San Francisco Bay Area, he contributes to projects that integrate complex algorithms and engineering principles.
Previous Experience in Data Science
Prior to his current position, Dan Frank held various roles in data science across multiple organizations. He worked as a Senior Staff Data Scientist at Coinbase from 2018 to 2022, where he focused on large-scale data products. Before that, he was a Senior Data Scientist at Airbnb from 2015 to 2018, and a Data Scientist at Yelp from 2014 to 2015. His early career included internships at Facebook and Twitter, where he gained foundational experience in data analytics.
Education and Expertise
Dan Frank has an extensive educational background in mathematics and engineering. He earned a Ph.D. in Computational Mathematics & Engineering and a Master of Science from Stanford University from 2011 to 2014. Additionally, he holds a Bachelor of Science in Applied Mathematics with an emphasis in Statistics & Economics from the University of California, Berkeley, completed in 2008. His academic training supports his specialization in machine learning, data science infrastructure, and statistical analysis.
Background in Analytics and Mathematics
Dan Frank's professional background includes a strong foundation in both computational and applied mathematics. He began his career as an Actuarial Analyst at Towers Perrin from 2008 to 2009, followed by a role as a Quantitative Analyst at The Climate Corporation from 2009 to 2011. His experience spans various sectors, allowing him to apply mathematical principles to solve real-world problems through data science.
Specialization in Data Science
Dan Frank specializes in several key areas within data science, including experimentation, causal inference, and machine learning. His expertise extends to building large-scale data products that effectively integrate algorithms, engineering, and mathematics. This specialization enables him to address complex challenges and contribute to innovative solutions in the field of data science.