Nick Elprin talks to Jon Krohn about how and when to scale a data science team and its workflows to secure a company’s commercial viability. You’ll also hear how to launch your own data science startup and why it’s so important to understand that AI tools are not one-size-fits-all.

This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and AWS Trainium (https://go.aws/3ycV6K0). Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn:
• How Nick served enterprises with his AI startup, Domino Data Lab [05:36]
• About the Navy’s own mine detection models [17:43]
• The hype surrounding GenAI [30:35]
• How AI platforms integrate with business strategies [39:49]
• When it’s time to integrate an AI tool into your business [51:12]
• Why Nick started Domino Data Lab [1:03:53]

Additional materials: www.superdatascience.com/811

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

811: Scaling Data Science Teams Effectively, with Nick Elprin

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 #data science teams