One of Winnipeg's finest data scientists talks about the skills that have helped him become successful (hint: doesn't involve memorize every hyper-parameter of every algorithm).
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[04:38] We talk about how Mark got into data science and the path that led him to where he is now.
[05:59] Mark talks about his awesome blog and how creating the blog helped him learn and grow as a data scientist.
[07:43] Mark tells us about Toastmasters and how being a part of that has helped him imporve his speaking skills and the benefits that a data scientist can gain from joining a Toastmasters club.
[11:00] He tell us a bit more about space repetition and how it's helped him learn more effectively.
[12:53] We discuss the similairties and differences between spaced repetition and deliberate practice, and Mark shares his tips for creating flashcards to help you quiz yourself.
[14:23] Mark talks to us about the hidden power of compouding and how all it takes to master anything is a solid plan of attack, time, and growth will occurr.
[17:50] He share some resources and blogs that expound on the concept of compounding.
[18:30] We get into what Mark's creative process is like for bringing his project ideas to reality and he shares tips for the up and coming data scientists who don't know where to start with their project.
[19:54] How he goes about identifying where to find data to start working on a project. He also talks about scraping the web for projects, some packages you can use for that, and some warnings so you don't get in trouble.
[21:47] Mark talks about how his idols shouted him out on their blog after he scraped their website and analyzed their posting behaviour.
[23:18] We get into another project that Mark worked on which involved analyzing data about trees from the City of Winnipeg open data portal.
[25:34] He also talks about some interesting and weird data that he's seen out there and then Mark talks about his framework for decision making and how this framework has helped him navigate the ambiguities of data science projects.
[27:30] How to use costs and benefits when making deciisons and find out how to best add value.
[28:32] Advice for people starting a new job as a data scientist and how to identify expectations and set expectations so that all parties involved are on the same page.
[29:47] How he describes his role to people within his organization who don't know what a data scientist is.
[30:48] The one thing Mark wants everyone to learn from his story.
[32:39] Getting into our lightning round - Python or R.
[32:58] A book he recommends every data scientist reads
[33:30] His favorite question to interviewee's ask during a job interview.
[34:05] Mark talks about the weird question he's been asked during an interview.
[34:36] Mark talks about his preference for self-directed learning and projects over certifications.
[35:19] How you can get in touch and connect with Mark online!