All The Things I Wish They Taught Us In Bootcamps | Eric Weber, PhD

On this episode of The Artists of Data Science, we get a chance to hear from Eric Weber, a lifelong learner, mathematician, and data scientist.

He has cultivated a passion for sharing his work and experience with others to help them become excited about data science, as well as educating executives on all aspects of data science.

He gives insight into his perspective of learning, how to be a leader in the data science field, and important skills that data scientists need to develop.

Eric shares with us what drew him to the field, and his transition from academia to the business side of data science.

This episode highlights the journey and success of someone who has seen the field develop from the beginning, and has continuously improved over time. I think there is a lot to learn from this conversation!

WHAT YOU WILL LEARN

[4:43] How to transition from academia to industry

[11:40] How to become a great data scientist

[20:59] How to communicate effectively with your team

[24:07] The art in science

[34:52] What soft skills you need

[41:15] What you should do about data science job descriptions

QUOTES

[6:35] "…my journey was all about figuring out two things. One, how to work with data at scale. And two, what does it mean to actually do data science in a business context. And those two things are really, really important…"

[12:17] "You don't need to build an incredibly powerful model for every situation, but you need to know what's going to allow the business to thrive in a productive way."

[19:48] …"getting by is not a long term solution to delivering value for a business, because what you're doing right now to get by is probably going to be automated in a few years…"

[23:50] "You're not always gonna be the expert in the room. And if you are, you're probably in the wrong room."

FIND ERIC ONLINE
LinkedIn: https://www.linkedin.com/in/eric-weber-060397b7/

Twitter: https://twitter.com/edweber1

[00:01:12] Introduction for our guest today

[00:04:17] How Eric broke into data science

[00:06:20] The challenges of transitioning from academia to industry

[00:08:21] Where do you see the field headed in the next two to five years

[00:09:16] Eric talks about the age of the specialist, and how its become the norm recently. He also talks about how this is now a "prove it" time for data science teams

[00:11:32] How to be a great data scientist

[00:12:54] Eric goes into detail about the need to deliver business value versus scientific value

[00:14:01] Data scientists are lifelong learners

[00:16:00] Why data science tends to be a more highly compensated field

[00:16:17] What's your advice to aspiring data scientists who feel like they have not learned enough to start applying for jobs?

[00:18:44] Why you never stop learning as a data scientist

[00:20:47] Don't be afraid to not know something

[00:22:09] The importance of finding teams where asking questions and being open is is valued

[00:23:59] The art of data science

[00:25:20] Curiosity and creativity in data science

[00:30:10] How to be a great leader in data science

[00:33:15] We talk about the book by Liz Wiseman called Multipliers

[00:34:36] The soft skills you need to succeed

[00:38:48] How could data scientists develop their business acumen and product sense?

[00:41:15] Don't be discouraged by these job descriptions

[00:43:28] Going from notebooks to productionizing models

[00:45:51] Why do we even build models in the first place? Mainly for two reasons, find out here.

[00:47:09] What's the one thing you want people to learn from your story?

[00:48:04] The lightning round