299: Becoming Seasoned At Failure

In this episode of the SuperDataScience Podcast, I chat with Head of Data Science and Machine Learning, Michelle Keim. You will hear what working remotely is all about in data science. You will learn about the importance of failure, and why everyone should lose their job at least once. You will hear about churn and segmentation, what they meant 10 years ago and what they mean now. You will also learn about the imposter syndrome and what to do when you feel like an imposter while applying for a role. You will hear about moving from centralized data science teams to integrated experts within the business and leading people on the three key learnings that Michelle has taken away from her experience as a leader. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/299

Om Podcasten

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.