The Artists of Data Science

For the last 20 years, Fred been lecturing on strategic thinking and complex problem solving; with an audience that has included the CEOs and management teams of major corporations and consulting firms around the world. Today he’s here to talk to us about his book. And share some tips with us on how we can be better problem solvers and more strategic. FIND FRED ONLINE Website: https://www.fredpelard.com/ LinkedIn: https://www.linkedin.com/in/fredpelard/ Twitter: https://twitter.com/fredpelard QUOTES [00:11:10] "When you're solving problems, you're starting point pretty much every time is going to be complexity. If it's not complex, it doesn't need solving" [00:14:05] "When your chest is puffed out, you know the answer. You're in expert mode." [00:17:58] "A lot of what these profession share is one similarity, which is a lot of the essence of their work is in the past. Lawyers solve past problems. Investigative journalists reveal past crimes. Engineersing actions build things in the present. But you see a theme emerging. None of these people really focus on the future. And so when you focus on the future, the data runs out of road and you have to use a different method." [00:20:29] "You don't need real Data to have real options. You need real Data to have real solutions. And that's one of the slight drawbacks of a lot of the people I work with who tend to be analytical in their mindset." [00:23:57] "I want to know which of my ideas is wrong early so I can reallocate my scarce time and resources towards the ones that work. And then once you've done that, now you feel very confident in your ideas." [00:25:17] "It's creative first and analytical second. So first, have lots of ideas about a problem in the future and then bring the cavalry of the data to sort of whittled them down to one." SHOW NOTES [00:01:35] Guest introduction [00:02:10] Where Fred grew up and what it was like there [00:03:15] What Fred was like in high school [00:03:45] The transition from rocket science to the business world [00:05:09] The inspiration for the book: How to Be Strategic [00:07:59] Being strategic is a mindset [00:10:47] Complexity, completion, clarity, certainty, and conviction. [00:13:43] The expert mode of problem solving [00:15:33] The analytical mode of problem solving [00:17:34] The creative mode of problem solving [00:20:29] Solutions versus options [00:21:29] And moving on now to the strategic method. Talk to us about that and maybe give us the example and some benefits like you're just doing. [00:27:51] The difference between qualitative and quantitative problems [00:30:28] Qualitative problems have a unique set of challenges [00:37:26] The power of positive framing [00:40:59] A twist on The Lean Startup Philosophy [00:49:10] Sell your ideas with impactful words [00:53:42] Memorable metrics [00:58:02] Road test your metrics [00:58:59] How to create a compelling story [01:02:30] It’s 100 years in the future, what do you want to be remembered for? [01:04:17] The Random RoundSpecial Guest: Fred Pelard.

The Data Science Happy Hours keep getting happier! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFw_ty92wJoWzoO7WlfaM7iYB8_qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/data_science_podcasts/

Dr. Busch is the Director of the Global Economy Program at New York University’s Center for Global Affairs where he teaches on purpose-driven leadership, impact entrepreneurship, social innovation, and emerging markets. Today he’s here to talk about his latest book “The Serendipity Mindset” – which develops a science-based framework for individuals and companies to help prompt and leverage positive accidents. FIND CHRISTIAN ONLINE WEBSITE: https://theserendipitymindset.com/ LINKEDIN: https://www.linkedin.com/in/christianwbusch/ TWITTER: https://twitter.com/ChrisSerendip QUOTES [00:05:09] "Serendipity is really this kind of smart luck. So, it's very different from the blind luck." [00:11:00] "In the end, it's all about connecting dots, right? It's all about saying, what is that kind of moment where, like you bring two potentially previously disparate things together." [00:14:03] "I think then essentially, once we overcome this bias to not underestimate the unexpected, we can create this muscle. That's the muscle that allows us to essentially make the best out of it." [00:15:45] "We all feel like impostors at times. We all feel like, you know, that we haven't figured it all out. And that's fine." [00:23:36] "I will still everyday talk with at least one other person to make them feel better about themselves. And by doing that, that gives me meaning. And I think that kind of reminded me, right, that in every situation you can always reframe something." [00:30:06] "The core idea is really that it's not only about knowledge that's power, but it's really kind of informational things that get seated. Then you can create knowledge out of it, unexpected." [00:33:58] "We create the most serendipity when we think constantly about how does this relate now to something I've read, to something I talked with a friend, and how can I introduce them to someone and something? " [00:41:50] "Serendipity is all about, somehow, sagacity. And it is all about kind of seeing something in the moment and making sense out of it. But, also then again, having the tenacity to to go through with it." [00:44:18] "I think the courage that comes from being vulnerable, and the courage that comes from admitting that you haven't had it all figured out then empowers other people as well. Because it gives them the license to come up with new ideas." SHOW NOTES [00:01:38] Guest introduction [00:02:51] What kind of kid were you in high school? [00:03:25] How different is life now than what you had imagined it would be? [00:04:07] what was the journey like from rebellious teenager to now Dr. Christian Busch? [00:05:00] How do you define serendipity? What is this thing? [00:06:32] The three types of serendipity [00:08:46] does serendipity have an anatomy? And if so, what does that anatomy look like? [00:10:50] The concept of bisociation [00:12:29] The biggest barriers to serendipity [00:14:03] The serendipity muscle [00:14:50] Alertness and serendipity [00:19:27] The importance of self-talk for serendipity [00:21:53] The reticular activating system and serendipity [00:24:43] How we can do a better job at defining problem statements [00:27:20] The two basic questions you should be asking [00:29:26] Information is at the core of life's opportunities [00:31:52] Networking in the COVID era [00:36:35] Remixing, rebooting and deconstruction [00:40:31] What can Seneca teach us about serendipity? [00:45:24] Why you shouldn’t be afraid to admit you don’t know something [00:50:44] How can we change the way that we speak to ensure that we're opening ourselves up for serendipity? [00:53:19] It's one hundred years in the future, what do you want to be remembered for? [00:55:38] The random roundSpecial Guest: Christian Busch.

The Data Science Happy Hours keep getting happier! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFw_ty92wJoWzoO7WlfaM7iYB8_qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/data_science_podcasts/Special Guests: Carlos Mercado and Santona Tuli, PhD.

Sundas is the first woman in her family to graduate university, earning her Bachelors from the University of Washington where she graduated as the class valedictorian. She’s currently a Senior Analytical Lead at Google. And before that she was a Data Scientist at Amazon, where she was awarded for her work driving large-scale experimentations and data science initiatives. FIND SUNDAS ONLINE Website: https://sundaskhalid.com/ LinkedIn: https://www.linkedin.com/in/sundaskhalid/ Medium: https://sundaskhalid.medium.com/ Twitter: https://twitter.com/sundaskhalid6 QUOTES [00:17:33] "A difference between a good and a great data scientist is communication. We know that Data science can be a complicated field. The purpose of doing all the data science work is so we can impact the bottom line of the business. And in order to do that, a lot of the times we have to pitch our own work to non tech individuals." [00:22:17] "In my life I have failed quite a bit of times. And every time I failed, I would get up again and try a different method. And try something else. And I will achieve it the second time, or the third time." [00:23:27] "Do not change your goal, change your method. And that's what this whole growth mindset is about. Keep learning and try different things. If it doesn't work one way, try a different way." [00:42:00] "You need to have a really good elevator pitch ready and you need to make sure that you have done the research on the person that you are reaching out to when you're cold messaging somebody." SHOW NOTES [00:01:35] Guest introduction [00:02:47] How Sundas got into data science [00:06:47] Sundas shares some of her struggles [00:10:25] Where is data science headed in the next two to five years? [00:12:49] What do you think will be the scariest application of data science in the near future? [00:14:16] The things you should be concerned with while working with data [00:17:22] What separates the good data scientists from the great data scientists? [00:18:31] The tutorial trap [00:21:31] The importance of embracing failure [00:23:27] The growth mindset [00:24:26] Sundas was rejected from a U of W and then got accepted and graduated as class valedictorian [00:26:07] How to deal with imposter syndrome [00:31:57] How can we foster the inclusion of women in data science? [00:34:53] What are some soft skills you need to succeed? [00:36:21] How to be a better storyteller [00:37:39] Executive communication for data scientist [00:38:34] Don’t be afraid of looking like you don’t know something [00:40:15] Tips on networking [00:44:27] Sundas talks about her career coaching services [00:45:44] We should be allies for underrepresented groups in data science [00:50:33] It’s 100 years in the future, what do you want to be remembered for? [00:51:50] The random roundSpecial Guest: Sundas Khalid.

The Data Science Happy Hours keep getting happier! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFw_ty92wJoWzoO7WlfaM7iYB8_qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/data_science_podcasts/

Keith is a sought after speaker, who routinely leads workshops at conferences. He’s given keynotes presentations at many international events and is an award winning instructor for UC Irvine's Predictive Analytics certificate program. You may recognize him as the instructor of thirteen courses on LinkedIn Learning - where’s taught over 250,000 learners through his courses. FIND KEITH ONLINE Website: http://www.keithmccormick.com/ Twitter: https://twitter.com/KMcCormickBlog AboutMe: https://about.me/keithmccormick Courses on LinkedIn Learning: https://www.linkedin.com/learning/instructors/keith-mccormick QUOTES [00:05:32] "What I concluded was that 2012 was really the big year where the dominos started to fall, that we're calling everything A.I. now." [00:08:28] "I think that most client organizations that I encounter, what they're missing, what prevents them from being effective is effective analytics middle management." [00:12:38] "Because you always have to rethink things between a prototype and putting it into production. So the notion that you're going to dismiss anyone that's using any tool other than coding in the same coding language that the team has adopted, you're working off a false premise" [00:14:10] "It seems to me there's an inherent flaw there, if the entire Data science community recognizes that the job descriptions are nuts and therefore everybody should ignore them." [00:15:39] "We put so much emphasis on the coding that there's this huge gap between running the code that creates something simple like a decision tree, and knowing the basic foundation and concepts of how the tree is growing and how to interpret it." [00:18:00] "I would say from the statistics side of the house, I want to know if they know when to trust and when not to trust the data. I'm really big on that." [00:20:35] "One thing I really don't like at all is when organizations use an external resource and they throw the data over the fence and then they just get the solution delivered on their desk. That's a nightmare." [00:22:39] "I think that before someone contemplates leaving their current department and joining the Data science team, they should never do that until they've done a project from start to finish as a borrowed resource." [00:31:53] "Your model is still degrading even if you're automatically rebuilding it. And the reason is that the model is only one step in a long process. You're also making assumptions about what data is relevant, what variables are used in the model, and all that." [00:48:03] "Part of the problem is none of us know what data science is, right. And by that I mean that it's a puzzle that we haven't figured out yet. It's the term is being used in so many different ways." SHOW NOTES [00:01:31] Guest introduction [00:02:45] Keith’s journey into data science [00:04:42] How much more hyped data science has become since the 90s [00:05:32] What the year 2012 did for data science [00:06:29] How tools of the trade have impacted data science adoption in recent years [00:07:45] Excellent project idea for anybody that's listening [00:08:15] In order to make machine learning work, we need to have effective teams [00:10:11] Diversity, recruiting, and data science teams [00:12:09] How does groupthink inhibit or limit team effectiveness? [00:13:27] Why hiring and retention in analytics is broken, and how to fix it [00:15:23] The essential checkboxes for a data science candidate [00:18:50] The challenges of being the first data scientist in an organization [00:21:52] Remixing talent inside your organization [00:23:57] What is the goal of analytics? [00:25:55] What are insights and how do we use them? [00:28:06] The goal of achieving a deployable model [00:30:53] What to do once the model is deployed [00:34:57] How to measure ROI on your data science projects [00:36:18] What are some steps that we could take to turn a business problem into a data science research question? [00:38:06] The difference between a consulting data scientist and an internal data scientist [00:41:07] Freelancing as a data scientist [00:45:32] How to be a good leader in data science [00:47:52] Is statistics the same as data science? [00:50:04] Embrace ambiguity [00:52:35] The skill of cognitive empathy [00:55:35] Why it's important that we have a commitment to our craft [00:57:28] How can we be more effective with our persuasion skills in Data science? [01:00:32] The most important part of the data science lifecycle [01:02:47] Why you need a little skepticism [01:05:26] It’s 100 years in the future, what do you want to be remembered for? [01:06:39] The random roundSpecial Guest: Keith McCormick.

It's the first Friday of the month! That means its time for a conversations episode! Kate Strachnyi is the founder of Story by Data & the DATAcated Academy. Story by Data is a LinkedIn content strategy for companies focused on innovation in artificial intelligence (AI), machine learning (ML), and data science. DATAcated Academy is a platform delivering training on data visualization best practices. Kate's a LinkedIn Top Voice in Data Science & Analytics (2018 & 2019) We have an excellent conversation talking about where she grew up, her early years, some the exciting projects she's worked on. We get to know Kate on a more personal level, and she shares things with us that she's never shared on any other podcast. Be sure to tune in!Special Guest: Kate Strachnyi.

The Data Science Happy Hours Holiday edition! You don't want to miss this one. We had some of the most influential names from the LinkedIn Data Science community in attendence! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFw_ty92wJoWzoO7WlfaM7iYB8_qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/data_science_podcasts/ Chat Transcript: http://theartistsofdatascience.fireside.fm/articles/oh14-chat-transcript SHOW NOTES [00:02:05] Work-life balance of a data scientist [00:06:27] “So, to answer your question, data science is just a regular ass job” [00:08:45] Hello to everyone who joined! [00:09:58] So many ways to learn, which one should I choose? [00:12:26] Moving from project management to data science [00:14:19] Dave share’s his perspective after 20 years in the data industry [00:16:18] Tips for being more active on LinkedIn [00:17:16] Susan – The Classification Guru – shares her tips for posting on LinkedIn [00:18:45] Giovanna shares her tips on being positive on LinkedIn [00:20:27] Greg Coquillo - LinkedIn Top Voice for Data Science 2020 – shares his tips on creating content and networking on LinkedIn [00:24:06] What are your tips for debugging code? [00:24:38] Liuna – Senior Data Scientist at IBM – shares her tips for debugging code [00:25:28] Srivatsan Srinivasan shares his tips on how to debug code [00:28:35] Carlos Mercado talks about Debugging in R [00:30:21] Monica Kay Royal shares her secrets for debugging code [00:31:15] George Firican shares some tips as well! [00:32:08] Joe Reis closes out the discussion on debugging [00:37:32] A big debate on the never end Python vs R question [00:42:47] What are your expectations from someone in a junior data scientist position? [00:43:14] Sarah shares what she’s looking for in a junior level candidate [00:44:42] What Srivatsan looks for in a junior data scientist [00:45:53] Monica, what do you look for in a junior data scientist? [00:46:39] What Vin Vashishta looks for in a junior data scientist? [00:47:51] Liuna what do you look for in a junior data scientist? [00:49:09] Mikiko what do you look for in a junior data scientist? [00:51:55] What does Kamrin look for in an junior data scientist? [00:53:39] How to stay motivated and re-evaluate your hustle when you’re in the job search? [00:56:24] Sarah shares some tips on turning applications into interviews [00:58:19] Mikiko shares some words of encouragement as well [01:01:17] Ben shares some advice on what to so with the crazy job descriptions [01:05:25] Jean-Sebastian shares some advice as well [01:08:25] Greg Coquillo adds to the discussion on what to do when you don’t hear back from applying for a job [01:10:13] Liuna closes out the discussion [01:11:51] Eric comes in and shares a LinkedIn hack. Also asks a question on scoring clusters [01:14:06] Dave has an answer to this tough question [01:17:06] Greg has a question on Federated Learning [01:27:13] Switching to python from a SAS background [01:34:04] We congratulate a member of the community on landing a job! [01:38:39] What’s the difference between a data scientist and a data analyst? [01:58:41] Why do you do these happy hours?Special Guests: Carlos Mercado, David Tello, Greg Coquillo, Mikiko Bazeley, Srivatsan Srinivasan, and Vin Vashishta.

The first solo episode ever - I hope you enjoy it! I also hope you enjoy the tunes I've put together for you to listen to as we wind down this week before the holidays! Tracks included in this episode (not in order): https://www.youtube.com/watch?v=2uAQjcVQdWw https://www.youtube.com/watch?v=9yX7P_IeiNQ https://www.youtube.com/watch?v=zkNXQUwHaDU https://www.youtube.com/watch?v=o6wRHQu9BgM https://www.youtube.com/watch?v=147A3e4rg1w https://www.youtube.com/watch?v=zaw2Y9mAOjw https://www.youtube.com/watch?v=A7MFfVraKx0 https://www.youtube.com/watch?v=gFhq0hJbJOw https://www.youtube.com/watch?v=_05nKCf7N9E https://www.youtube.com/watch?v=yTgXHQPcYSs https://www.youtube.com/watch?v=1GLEJEYDdfg