Kaggle competitions, and data science courses for that matter, focus on the technical skills required to be a data scientist.
This is understandable to some extent, but a data scientist must be able to think like a statistician, a scientist, a customer, and a software developer, sometimes in the same meeting!
This is especially true in organisations where data science is a new function, which is most organisations. So what are the "soft skills" that we don't talk as much about and can these even be taught? What makes a good vs. bad data science hire?
In this talk we'll explore the other side of the data science “stack” - the skills and techniques that complement your technical knowledge and are at least as important to succeed.
About the Speaker:
David Asboth is a data scientist, educator, former software developer, and a City, University of London alumnus.
He currently works as a freelance data science instructor, teaching short and long courses in data science at General Assembly.
These days he spends his time figuring out what aspiring data scientists actually need to know.
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