Charles shares with us his journey into becoming a prolific author, and why he decided to write Naked Economics, Naked Statistics, and so on. He also warns the use of big data and the implications it can have if used improperly. This episode is packed with insights into money, statistics, and some of the important problems the world is currently facing.

WHAT YOU'LL LEARN

[4:25] Charles’s tips on learning a subject effectively

[12:41] What is money, and why does it matter?

[21:40] How statistics can be used to make solve problems

[26:55] Why humans are so bad at appreciating and conceptualizing probabilities

[33:02] Important soft skills that technically oriented people need

QUOTES

[11:56] “Big Data is...a powerful weapon...it really can be put to great effect. Used improperly, you can do some enormous damage.”

[33:07] “...even if you are very technically oriented, you have got to have an awareness of sociology, psychology, great literature and the like.”

[36:23] “...if your data reflects some underlying problem, then any model you build from that data will just embed it more firmly in cement.”

[48:15] …”stop thinking about what you're doing and look around the world and see what's missing”

FIND CHARLES ONLINE

LinkedIn: https://www.linkedin.com/in/charles-wheelan-a6220911/

Website: http://www.nakedeconomics.com/

Twitter: https://twitter.com/CharlesWheelan

SHOW NOTES
[00:01:19] Introduction for our guest

[00:02:45] How did you become so interested in statistics?

[00:04:16] Was there a lot of self study involved in learning statistics?

[00:05:06] How he wrote Naked Statistics

[00:06:51] What is economics?

[00:09:19] Does big data impact how economics works?

[00:11:21] Does big data change how the invisible hand works?

[00:12:35] What is money and why does it matter?

[00:16:43] Money in a world of contactless payments

[00:18:18] The impact of digital currencies on society

[00:20:15] Money and intersubjective reality

[00:21:22] How to use statistics to make business work better

[00:23:12] Which form of bias should we be most wary of?

[00:24:40] How will COVID affect the election

[00:26:49] Why are humans so bad at appreciating conceptualizing probabilities?

[00:29:26] Why is it important that we cultivate an intuition for what probabilities represent?

[00:30:39] Why we shouldn't buy the extended warranty

[00:32:38] What's going to separate them from the rest of the world, the rest the competition.

[00:32:54] What soft skills do you need to be successful?

[00:37:19] Charles Wheelan predicted COVID in his book The Rationing

[00:37:37] Draw parallels between the fiction you wrote and the reality that we're experiencing today

[00:39:03] How he came up with the story for The Rationing

[00:41:07] Which aspect of human nature do you think from your fiction has shown itself to become a reality with our current situation?

[00:43:18] What's the one thing you want people to learn from this story?

[00:44:35] The lightning round

Special Guest: Charles Wheelan, PhD.

Scott shares with us his incredible career journey and the insights he has gathered from it. This episode is packed with advice, wisdom, and tips for every data scientist to take something from. It was a great honor interviewing Scott!

WHAT YOU'LL LEARN

[7:57] What is an A.I. winter?

[10:54] Where the field of data science is headed in the next few years?

[13:58] Tips on being an effective leader

[20:39] The underrated skill of storytelling, and how to cultivate it

[32:43] Tips for people that want to break into data science

QUOTES

[16:01] “If you're the first data scientist in an organization...make sure that you focus on a crawl, walk, run approach.”

[17:50] “Simplicity is ridiculously underrated…people do not support what they don't understand. Instead, they fear what they don't understand.”

[35:03] “Find your why and make sure it's the right why and use that to propel you…”

SHOW NOTES

[00:01:35] Introduction for our guest today

[00:03:33] What drew you to the field and some of the challenges you faced while you're trying to break into and create your own lane in Data science?

[00:05:00] How much more hyped has I become since he first broke into the field?

[00:07:39] A brief history of the AI winters we've experienced and why we're on the verge of the next winter

[00:10:54] Where do you see the field of data science, machine learning, artificial intelligence headed in the next two to five years?

[00:12:27] In this vision of the future. What do you think is going to separate the great Data scientists from just the good ones?

[00:13:42] What's it mean for you to be a good leader in Data science. And how can an individual contributor embody the characteristics of a good leader without necessarily having the title?

[00:15:27] For someone who's, let's say, the first data scientist in the organization and they're kind of responsible for building up to Data Science practice, what are some of the challenges that you would see them facing and how do you think that they could overcome those challenges?

[00:18:48] What would you say the hero's journey looks like for a Data scientist or anyone in a data related role?

[00:19:31] The importance of story-telling in data science

[00:22:27] Does the way you tell a story differ if you're talking to your manager versus maybe talking to a roomful of executives? Do you have any tips for Data scientists?

[00:25:32] So what are some questions we could ask ourselves when we're starting a project that can really help us clarify exactly what the problem is?

[00:27:35] There is a hidden Data science message in the movie Dr. Strange

[00:28:47] How do you think a Data scientists could develop and cultivate a business acumen or a product sense for themselves?

[00:30:56] The multiplicity of algorithims and the importance of feature engineering

[00:32:25] Can you share some tips or words of encouragement for our listeners who's got like a couple of decades, maybe 10 to 20 years of non Data related experience under their belt and they're now trying to break into Data science? What challenges do you foresee them facing and how can they overcome these challenges?

[00:35:20] What advice or insight can you share with people who are breaking into the field and they look at these job postings and some of them want the abilities of an entire team wrapped up into one person?

[00:39:28] Do you have any suggestions for finance or fintech Data science projects that an aspiring Data scientists could tackle?

[00:42:15] What are some things that we need to be cognizant of and monitor and track once the model is deployed, both from the Data scientists perspective and the business perspective?

[00:44:22] What advice do you have for Data scientists who have who feel like they don't need to learn anymore? What would you have to say today, scientists in that mindset?

[00:46:51] What's the one thing you want people to learn from your story?

[00:48:58] So what are the two five letter words that really grind your gears and why?

[00:49:06] So what is an academic topic or just an area of research or interest outside of Data science that you think every Data scientist should spend more time researching on?

[00:49:27] What is your favorite question to ask during an interview?

[00:51:00] What's the number one book you'd recommend our audience read and your most impactful take away from it?

[00:52:08] If we could somehow get a magic telephone that allowed us to contact 20 year old T. Scott, what would you tell him?

[00:52:42] What is the best advice you have ever received?

[00:53:09] What motivates you?

[00:53:35] What song do you have on Repeat right now?

[00:53:44] How could people connect with you? Where can they find you?

Special Guest: T. Scott Clendaniel.

You may know Joshua from his youtube channel StatQuest, where he's beloved by his audience of over 320,000 subscribers and 15 million viewers.

Joshua shares with us his powerful journey from being a cellist and music composer to getting his PhD in computational biology and then creating StatQuest.

This episode is packed with advice, wisdom, and tips for developing a creative process and facing your fears. It was a great honor interviewing Joshua!

WHAT YOU'LL LEARN

[9:05] How music has helped Joshua become more creative

[17:19] Inspiration for StatQuest

[24:00] The most challenging part of creating content

[28:02] The most misunderstood concept from statistics and machine learning

[36:38] How Joshua approaches his creative endeavours

QUOTES

[9:38] "I pick up my guitar, my ukulele, and I start playing, and my head just completely clears."

[19:52] "what I really want people to take home is that anyone can understand these things [statistics]. Ninety nine times out of 100, the only thing between them and understanding is fancy terminology and fancy notation"

[23:31] "It's probably a good thing that I'm a little nervous…because it pushes me just a little harder to make sure that what I'm talking about is correct"

[33:16] "…if you want to educate someone…you have to relate with them and you have to see the material from their perspective."

FIND JOSHUA ONLINE

LinkedIn: https://www.linkedin.com/in/joshua-starmer-95a554130/

YouTube: https://www.youtube.com/user/joshstarmer

Website: https://statquest.org/

SHOW NOTES

[00:01:40] Introduction for our guest

[00:03:13] How Joshua got into statistics

[00:04:12] Where do you see the field of Data science headed in the next two to five years?

[00:05:12] What do you think is gonna separate the great Data scientists from the really good ones?

[00:06:22] Talk to us a bit about what music theory is, what a music theorist does.

[00:08:59] Do you think having a deep understanding of math has helped you be more creative as a musician or vice versa?

[00:11:22] What are some of the commercials and shows that feature your music?

[00:15:32] Joshua describes his process for creating music

[00:17:12] The inspiration of StatQuest

[00:19:27] The StatQuest mission

[00:20:40] Overcoming the resistance when it comes to creating and publishing content

[00:23:53] What's the most challenging part for you when it comes to creating content for the channel?

[00:25:15] What's your personal favorite video from the archives?

[00:26:16] The absolute must watch video from StatQuest

[00:27:53] The most misunderstood statistical concept

[00:30:23] Why you don't need to memorize forumals

[00:32:37] Can you recommend a good book for learning statistics?

[00:34:27] The art and science of data science

[00:36:25] Creativity and data science

[00:38:05] What would you say are the similarities and differences in the creative process for, let's say, writing a research publication, composing music or creating youtube video?

[00:39:38] What's the one thing you want people to learn from your story?

[00:40:47] The lightning round.

Special Guest: Joshua Starmer, PhD.

He's the author of Lean Analytics, when we co-wrote with Benjamin Yoskovitz. He's also one of the founders of Coradiant, Year One Labs, and the Strata confersence.

He shares some excellent tips one how to ask the right questions when working with data, essentials of business communication, and the need to be obsessed as an entrepreneur.

WHAT YOU WILL LEARN:

[28:28] How to be an intrepreneur

[13:39] Incorporate philosophy with data

[19:11] Why you need to be obsessed as an entrepreneur

QUOTES

[14:22] …”as an early stage company, your focus is your biggest currency.”
[22:10] …”crises have a way of accelerating the inevitable.”
[46:04] “...you got to first seek to engage and entertain and then you have the ability to inform people.”
[51:38] …”find a way to capture attention that you can turn into profitable demand better than the competition.”

WHERE TO FIND ALISTAIR ONLINE:

Twitter:https://twitter.com/acroll
LinkedIn:https://www.linkedin.com/in/alistaircroll/
Website: http://solveforinteresting.com/

SHOW NOTES
[00:01:37] Introduction for our guest today

[00:03:20] Alistair talks about his early work with Coradiant

[00:05:47] What do you think the next two to five years is going to look like for businesses leveraging data and analytics?

[00:07:55] Why A.I. will need a therapist

[00:08:26] In this new vision of the future then what's really going to separate, like the great data scientists from just the merely good ones?

[00:11:03] The importance of privacy and GDPR for data scientists

[00:13:56] The concept of "one metric that matters" and how that's going to manifest in terms ofmeasuring privacy

[00:15:00] Why Zoom DOES NOT deserve to be the videoconferencing platform in the world

[00:17:30] Do you have any advice or tips for anyone who's been toying with the idea of entrepreneurship?

[00:19:22] Why we need to instill leaps of faith in people who want to be founders

[00:21:06] In terms of data science, entrepreneurship in this COVID/post-COVID area. What do you see as some problems with tackling that in enterprising data? Scientists can can identify and then get into an opportunity?

[00:22:29]So you've been writing a lot about innovation at Tilt to the Windmill. How should be incumbents think about innovation?

[00:23:02]A deep dive into various models of innovation

[00:26:38] An excellent and thorough discussion on intrapreneur

[00:30:37] Some great advice for one man data science teams who are on an intrapreneurial journey

[00:33:50] The stages of growth intrapreneur developing data products within their organization will face and how to overcome challenges in those stages

[00:36:50] We get into music science and its intersection with data science

[00:43:13] What's your go to music?

[00:43:54] The important soft-skills that a data scientist needs for success

[00:47:11] What are some key takeaways from your book - Propose, Prepare, Present - that you think a data scientist should apply when communicating with non-technical audiences?

[00:49:27] Let's talk a bit about being evil. You say start-ups should be more evil, that sounds terrible. What are you thinking? What are you trying to communicate with that?

[00:53:23] What's the one thing you want people to learn from your story?

[00:54:24] What's it mean to solve for interesting?

[00:56:00] Jumping into a quick lightning round: What would be the number one book, other fiction or non-fiction or both that you'd recommend our audience read and your most impactful takeaway from it?

[00:57:19] If we could somehow get a magical telephone that allowed you to contact 18 year old Allistair. What would you tell him?

[00:58:45] What it means to cultivate a personality

[01:00:07] What's something you've done at one of your ventures that's been just evil enough?

[01:02:57] What's the best advice you've ever received?

[01:04:58] What motivates you?

[01:06:10]So what song do you currently have on repeat?

[01:06:34] How could people connect with you? Where can they find you?

Special Guest: Alistair Croll.

He has spread the gospel of digital transformation through public speaking engagements, blogs, videos, white papers, podcasts, puppet shows, cartoons and all forms of verbal and written communications. He has also helped organizations, such as Microsoft and Nielsen, comb through and organize their data for meaningful use.

Scott shares his "eight 'ates of master data", a set of rules to engage with master data in a meaningful way. He also goes over his tips for communicating with executives, along with important soft skills that are being overlooked by data scientists.

Scott is very articulate, and his passion for data and teaching are definitely evident in this episode!

WHAT YOU WILL LEARN

[12:57] The eight 'ates of master data management

[17:04] Data science communication with executives

[21:45] Legacy data systems

QUOTES
[3:37] "It's not all about building. Sometimes it's about making sure things are structured and organized the right way."

[7:11] "Hardware comes and goes. Software comes and goes. Data always remains."

[16:11] "Data, to have value, has got to be in motion."

[20:36] "If you're a data scientist, you are the business….and it's impossible for you to learn too much about your own business."

[27:08] "…you've got to bring people from "I have no idea what you're talking about" to "how can we live without this?" and that comes from telling a good story."

WHERE TO FIND SCOTT ONLINE

LinkedIn: https://www.linkedin.com/in/scottmztaylor/

Twitter: https://twitter.com/stdatawhisperer

Website: https://www.metametaconsulting.com/

SHOW NOTES
[00:01:20] The introduction for our guest today

[00:02:54] Scott talk to us a bit about his professional journey, how he got involved in the data world. And what drew him to this field?

[00:04:40] Scott talks to us about some of the early gigs he had in the data space.

[00:05:54] Where do you see kind of the field of big data and digital transformation? What's this landscape going to look like in two to five years?

[00:07:41] Scott talks about how the stakes are changing and how data management is unavoidable

[00:08:32] Scott goes more in-depth as to how the stakes are changing and how he's seen it play out across enterprise organizations.

[00:09:56] In this vision of the future where the stakes are changing, what do you think is going to separate the great data professionals from the merely good ones?

[00:11:25] Scott takes us through what he calls the "eight 'Ates" of data: Relate, Aggregrate, Validate, Integrate, Interoperate, Evaluate, Communicate, Circulate

[00:16:29] Scott breaks down how to effectively communicate with executives and what they care about - hint: not necessarily what you care about as a data scientist

[00:18:27] Scott shares some tips for data scientists coming into organizations with legacy organizations and how to navigate that landscape

[00:21:11] What are the similarities or differences in the challenges a legacy system organization faces versus a tech startup? And how can one navigate these waves?

[00:23:40] So what would you say is the biggest data blunder in the last year or two? He describes the system of hotel keys and how it relates to master data, very interesting!

[00:25:12] So what about some data wonders? He describes an everyday application of a wonder: the checkout counter at a grocery store.

[00:26:41] More insight on communicating with stakeholders and executives

[00:27:56] What are some of the soft skills that that candidates are missing that are really going to separate them from the competition?

[00:29:29] There's a lot of people out there who are trying to break into the data space and maybe they feel like they don't belong there or know enough for they aren't smart enough. Do you have any words of encouragement for them?

[00:31:20] Scott does a deep dive into his passion for data and how you can cultivate it in yourself

[00:33:02] What's the one thing you want people to learn from your story?

[00:34:21] The lightning round

Special Guest: Scott Taylor.