Jon Krohn speaks with Shashank Kalanithi, the man who makes a sport out of YouTube and data analytics out of sports. Listen in as he talks about how he got started producing YouTube videos on data science, the essential differences between data science roles, and how data could shape the future of the sports industry.

This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• What motivated Shashank to start his YouTube channel [04:31]
• The must-have technical skills for every data scientist [16:59]
• The soft skills needed for data science [20:52]
• The differences between data analyst, data scientist and data engineer [24:26]
• How data are currently being applied in the sports industry [38:38]
• The “needs” divide between digital native and traditional companies [45:34]

Additional materials: www.superdatascience.com/623

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

623: Data Analyst, Data Scientist, and Data Engineer Career Paths

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.

623: Data Analyst, Data Scientist, and Data Engineer Career Paths

Super Data Science: ML & AI Podcast with Jon Krohn