Marck Vaisman speaks to Jon Krohn about his paradigm for understanding core data practitioner types. Hear Marck detail the four data practitioner personas that he has identified in his research, why he believes the roadmaps that influencers like to promote as surefire ways to a data science career don’t work in practice, and why the term “data scientist” is still so elusive and hard to recruit for.

This episode is brought to you by Gurobi (https://www.gurobi.com/personas/optimization-for-data-scientists), the Decision Intelligence Leader. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn:
• How Marck started his work in defining data science roles [08:06]
• The relationship between the four data practitioner personas [15:26]
• About Marck’s “menu” for effective data science [40:43]
• How recruiters can hire the best data scientist for the job [59:31]

Additional materials: www.superdatascience.com/821

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

821: The Skills You Need to Be an Effective Data Scientist, with Marck Vaisman

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 #Effective Data Scientist