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Dan Frank has a diverse work experience in the field of data science and analytics. Dan is currently working as a Staff Data Scientist at Watershed since 2022. Prior to that, from 2020 to 2022, they served as an Advisor for Data Science at Transform. Dan also worked at Coinbase as a Senior Staff Data Scientist from 2018 to 2022.

Before joining Coinbase, Dan worked at Airbnb as a Senior Data Scientist from 2015 to 2018. During their tenure at Airbnb, they established and headed the Data Science presence on the Infrastructure team. Dan played a key role in various projects, including variance reduction, market level effects, and (meta)analysis automation. Dan also developed several tooling across the Data Science organization.

Prior to Airbnb, Dan worked at Yelp as a Data Scientist from 2014 to 2015. Dan founded and grew the Data Science team within Yelp, defining team roles, projects, and infrastructure. Dan also authored publicly facing blog posts and news stories for Yelp. Dan'sprojects at Yelp included engagement/churn analysis, predictive models embedded in product features, user clustering, metric validation, interactive visualization, and experimental infrastructure.

Dan's career began as a Graduate Student at Stanford University from 2011 to 2014. During this time, they focused on their studies and research. Dan also gained industry experience as an intern at Facebook in 2013, where they implemented predictive algorithms and created frameworks for evaluating custom options in the context of budget allocation. Dan also interned at Twitter in 2012, where they designed an end-to-end system for Twitter event detection and established version control and repository management practices for research code.

Before their graduate studies, Dan worked as a Quantitative Analyst at The Climate Corporation from 2009 to 2011. Dan'swork involved developing statistical models for automated pricing of weather derivatives and portfolio risk management. Dan also optimized clients' weather insurance portfolios relative to historical crop yields.

Dan's early career includes a role as an Actuarial Analyst at Towers Perrin from 2008 to 2009, where they gained experience in actuarial analysis.

Overall, Dan Frank has a strong background in data science and analytics, with experience in various industries including technology, finance, and agriculture. Dan has demonstrated expertise in project management, team leadership, and the development of innovative data-driven solutions.

Dan Frank attended Stanford University from 2011 to 2014, during which they obtained a Master of Science (M.S.) and a Doctor of Philosophy (Ph.D.) degree in Computational Mathematics and Engineering. Prior to that, they attended the University of California, Berkeley from 2004 to 2008, where they earned a Bachelor of Science (B.S.) degree in Applied Mathematics with an emphasis in Statistics and Economics.