621: Blockchains and Cryptocurrencies: Analytics and Data Applications

Cryptocurrency and blockchain take center stage this week as we welcome Chief Economist at Chainalysis, Philip Gradwell, to discuss the data science applications in this exciting field. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform, by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts, and by Bunch (superdatascience.com/bunch), the AI driven leadership coach. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What the role of a chief economist entails [5:50] • What are blockchains and cryptocurrency? [8:23] • How analyzing cryptocurrencies differs from established fiat currencies [12:48] • Philip's work at Chainalysis [26:07] • Philip's crypto data analytics pipeline [34:48] • How Philip develops data products for a wide range of users [46:18] • How the blockchain facilitates innovative computing and machine learning technologies [51:52] • What Philip looks for in the data scientists he hires [1:04:59] Additional materials: www.superdatascience.com/621

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The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.