On this episode of The Artists of Data Science, we get a chance to hear from Kyle McKiou, a data scientist who took the lessons from his own struggles that he faced attempting to break into data science and packaged them into a course for up and coming data scientists.
He is known for his remarkable talent for building skilled, balanced and productive teams. He gives insight into how he broke into the data science field, his approach for problem solving, and they importance of facing your fears.
Kyle shares with us the importance of finding a mentor that can guide you to accomplish your goals and the important soft skills that you may be overlooking. Kyle brings unprecedented wisdom and advice to this episode, and the points he outlines can help everyone step up their professional goals.
WHAT YOU WILL LEARN
[7:43] What value Kyle believes data science will bring within the next few years
[11:38] How to transition into data science
[16:33] The importance of cultivating a growth mindset
[28:30] Soft skills that data science candidates are missing
[33:01] The single biggest myth about breaking into data science
[16:13] "Be risk averse; Test everything."
[24:50] "You've got to engineer a system that solves the problem for you, because if you have to leverage your own intelligence to solve a problem, well, you're going to be very limited in the amount of work that you can do."
[27:23] "…you start with the problem you want to solve. You break it down to simpler problems. You break those problems down to simpler problems…all the way back until you get to your present state and then you see the exact path forward at any point time…"
[28:31] "…I think in most careers it's not going to be the hard skills that separate you, particularly in data science…[it's] those soft skills, because you realize that if you want to make an impact in the company as a scientist, you're going to need other people to work with you…"
[34:55] "…it doesn't matter how much you know, it matters how much you can learn and adapt."
FIND KYLE ONLINE
Data Science Dream Job: https://dsdj.co/artists70
[01:30] Introduction of our guest today
[03:10] Talk to us a little bit about how you first heard data science and what drew you to the field
[4:50] How software engineering is different from data science
[06:42] What do you love most about the field of data science?
[07:29] Why do you think the field is headed the next two to five years?
[09:46] What do you think is in the separate the great data scientists from the merely good ones?
[11:21] Switching from software engineering to data science
[12:42] How to productionize a machine learning model
[13:19] Why notebooks don't scale
[16:18] The importance of the growth mindset for data scientists
[19:38] Fear as an indicator
[24:29] The engineers mindset for data science
[28:30] Soft skills for data science
[33:01] The biggest myth about breaking into data science
[35:00] Poker and data science
[37:07] What's the one thing you want people to learn from your story?
[39:17] The lightning round