Angel investor and data science consultant Josh Wills sits down with Jon Krohn to discuss his former roles (Google, Slack, and Cloudera) and the essential skills for engineering scalable machine learning projects.

This episode is brought to you by Pathway, the reactive data processing framework (www.pathway.com/?from=superdatascience), and by epic LinkedIn Learning instructor Keith McCormick(https://linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• Josh's 'Data Engineering for Machine Learning' course [06:50]
• Contextual bandits [10:52]
• Data quality and monitoring [16:45]
• The “infinite loop of sadness” in data product development [25:12]
• Josh’s definition of a data scientist [30:02]
• Josh's role at WeaveGrid [37:36]
• Management-Track vs Independent Contributor [48:47]
• Josh's work on the Covid pandemic [1:06:46] 
• Josh’s favorite tech stack [1:11:13]

Additional materials: www.superdatascience.com/665

The Super Data Science Podcast: Machine Learning | AI | Success

665: How to be both socially impactful and financially successful in your data career

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.

New tracks tagged #Successful Data Career