How to Build a Data Science Culture | John K Thompson


April 16th, 2021

1 hr 14 mins 40 secs

Season 11

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About this Episode


He has experience building start-up organizations from the ground up and has reengineered business units of Fortune 500 firms to enable them to reach their full potential.





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[00:07:27] "We, as data scientists, understand data drift and model drift very well. But most people outside the field don't. So they say is: 'I hired these people. They built a model. That should be the end of it. It should work into the future and forever. And as we know, they don't"

[00:15:16] "Oh, it's definitely an art. There's no doubt about science is a creative endeavor. It is an artistic endeavor."

[00:26:22] "And I've said it many times. You probably heard me say it before. We are Data scientists. We are not magicians. We can't just make stuff up. We have to have something to work with.."

[00:30:02] "An open mindset is really, in my opinion, is often characterized and exhibited by a voracious curiosity."

[00:31:34] " I've often seen people through my career - and they generally don't do very well in data science - that they think they know everything. And they think they know how to approach every problem..."


[00:01:27] Guest introduction

[00:02:51] A general data science problem solving framework

[00:08:48] Artisanal vs factory data science teams

[00:13:23] How does the artisanal or factory culture happen on data science teams?

[00:15:13] Is Data science and art or science? How do you view it?

[00:17:47] The creative process in data science

[00:20:21] Phase separation in data science

[00:22:10] How to manage executive expectation when a fair chunk of data science is research

[00:24:47] Help us understand what is a good idea? What is a bad idea? What separates the two?

[00:28:02] What to do when you’re working on a problem but nothing seems to work

[00:29:35] Open mindset vs fixed mindset

[00:32:50] Ditch the map, use a compass

the story? Yeah, we do think there's a there's a future in those computers.

[00:35:39] Where do you see the field of Data things headed in the next two to five years?

[00:38:47] What was your journey like going from an individual contributor to executive level?

[00:41:17] What makes analytics so unique?

[00:42:33] How would you handle that situation where you have somebody who thinks they know your job and is trying to tell you what to do and not to do?

[00:45:57] Learn to build, learn to sell.

[00:48:01] How to become a better communicator

[00:51:06] As the first data scientist in an organization, how can we ensure that we're building or at least cultivating a culture for analytics to thrive?

[00:53:31] How can we balance and this creative, iterative, unpredictable process of analytic discovery with those environments that have these operational or production process-oriented characteristics?

[00:55:59] Does agile development practices work on data science teams

[00:58:20] Linear and non-linear thinking

[01:01:23] Where on the org chart do data science teams belong?

[01:04:23] What are some unreasonable expectations that executives and management have of startup data science teams?

[01:08:15] It is one hundred years in the future, what do you want to be remembered for?

[01:08:46] The Random Round

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