The Artists of Data Science

Vote in the data community content creators awards! http://bit.ly/data-creators-awards Check it out and don't forget to register for future office hours: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh 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 [00:03:27] What are examples of times when you think that Data is not an appropriate solution to the problem? [00:05:08] If one is trying to force Data to solve a business problem where it doesn't belong, then that is not a great approach for any problem solving. [00:08:53] Data itself shouldn't lead to anything. [00:16:35] A question around end-to-end data projects, specifically how to approach planning one. [00:19:28] Thom Ives shares how to think through a project pipeline [00:23:39] Ben Taylor talks about how to approach a project [00:24:47] A corporate perspective for planning a project [00:28:36] Antonio with a mic drop [00:30:57] Which LinkedIn post would become an NFT in the future? [00:37:03] What is the biggest pain points in your process, that if you alleviate with a magic wand, would make your life soooo much easier? [00:38:37] Ben Taylor chimes in with some insight to this question [00:41:59] Antonio: I think this is all communication. Honestly, ninety five percent of the problems I see are related to the communication rather than technology [00:47:41] The importance of MLOps and documentation [00:51:38] As a manager for one silo, you are not understanding the other silo and therefore you're not able to communicate through language barriers. [00:53:07] Even if I know the answer, I'll still ask those questions so that I can benefit, or maybe somebody else can benefit from it. [00:56:18] Thom has a conspiracy theory about David Langer [00:56:51] What do you think is the next wave in data science? [01:04:52] Data Science is such a broad field, and I don’t know If I am I technical enough [01:06:13] Santona: I think technical ability is so vague and broad and very context specific [01:09:01] Mikiko shares some awesome advice [01:12:22] Greg: And what I can tell you is if you focus on gaining industry knowledge, you will be so comfortable with tackling what needs to be done from the technical side to solve these business problems. So the more business savvy you are, the better you can communicate with business folks, identify their problems, then you can work backwards to figure out you need technical skills that you need to solve them. [01:13:25] Specialize or generalize? [01:15:05] What are the things that school can't teach you? Special Guests: Kate Strachnyi, Kurtis Pykes, Mikiko Bazeley, and Santona Tuli, PhD.

Comet provides a self-hosted and cloud-based meta machine learning platform allowing data scientists and teams to track, compare, explain and optimize experiments and models. Backed by thousands of users and multiple Fortune 100 companies, Comet provides insights and data to build better, more accurate AI models while improving productivity, collaboration and visibility across teams. Register for future sessions here: http://bit.ly/comet-ml-oh Checkout Comet ML by visiting: https://www.comet.ml/ Checkout the latest FREE e-book from Comet - Building Effective Machine Learning Teams: https://bit.ly/3bWrJ0O Or on Twitter: https://twitter.com/CometML On YouTube: https://www.youtube.com/channel/UCmN63HKvfXSCS-UwVwmK8Hw Connect with Ayodele LinkedIn: https://www.linkedin.com/in/ayodeleodubela/ Twitter: https://twitter.com/DataSciBae Check out her course on LinkedIn Learning: https://www.linkedin.com/learning/supervised-learning-essential-training/supervised-machine-learning-and-the-technology-boom

Evan is a #1-ranked recruiter and former C level talent executive with numerous awards. He’s taken his years of experience and distilled it into a groundbreaking hands-on, proven, scientific approach to cracking job interviews. His book reveals a science that, when learned and practiced aggressively will allow you to go on the offensive. Controlling and creating the interview the way you want it, while answering all of the hiring manager’s questions - often before they’re asked. And today he’s here to share some tips with us so that we’re ready to crush our next interview! FIND EVAN ONLINE LINKEDIN: https://www.linkedin.com/in/evan-pellett-008a108/ TWITTER: https://twitter.com/HowToInterview1 Apologies on the audio quality here - I was having microphone issues HIGHLIGHTS FROM THE SHOW [00:01:42] Guest Introduction [00:03:15] Evan talks about his early years [00:03:54] How is life different from what you thought it would be? [00:04:49] What is industrial psychology? [00:05:55] How Evan’s journey inspired his writing of his book [00:09:21] The eight-step process for a successful interview: REAP RICH [00:16:11] How do you make sure that we're demonstrating that we produced strong results in the past? [00:20:10] What can we do to make sure our energy is on point during an interview. How do we take that nervousness and make into something positive? [00:22:55] Handle your inner states [00:29:19] Tend to your inner landscape [00:32:39] How do we demonstrate our growth mindset in the interview process? [00:38:33] How can extracurricular activities help your profile in the job search? [00:39:17] Yes, definitely. And and that's a very strong piece of it, because what they want to know, what makes you work harder, be more creative. [00:40:57] A framework for telling stories and communicating results in an interview [00:47:24] The question behind the question [00:50:08] What type of questions should you ask during an interview? [00:55:13] How to ask for the job [01:00:13] The biggest thing you’re failing to do throughout your career [01:05:06] How to control the flow of an interview [01:09:03] Create connection in the interview [01:10:03] What is subtle defiance and how do we prevent ourselves from being that? [01:16:56] There are four types of hiring managers, here are their profiles? [01:22:25] It’s 100 years in the future, what do you want to be remembered for? [01:23:35] The Random RoundSpecial Guest: Evan Pellett.

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 Register for Sunday Sessions here: http://bit.ly/comet-ml-oh 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_qjmSpecial Guests: Greg Coquillo and Nicole Janeway Bills.

Comet provides a self-hosted and cloud-based meta machine learning platform allowing data scientists and teams to track, compare, explain and optimize experiments and models. Backed by thousands of users and multiple Fortune 100 companies, Comet provides insights and data to build better, more accurate AI models while improving productivity, collaboration and visibility across teams. Register for future sessions here: http://bit.ly/comet-ml-oh Checkout Comet ML by visiting: https://www.comet.ml/ Or on Twitter: https://twitter.com/CometML On YouTube: https://www.youtube.com/channel/UCmN63HKvfXSCS-UwVwmK8Hw Connect with Ayodele LinkedIn: https://www.linkedin.com/in/ayodeleodubela/ Twitter: https://twitter.com/DataSciBae Check out her course on LinkedIn Learning: https://www.linkedin.com/learning/supervised-learning-essential-training/supervised-machine-learning-and-the-technology-boom HIGHLIGHTS FROM THE SESSION [00:02:21] What does it mean to be an expert in Data science? What's that spectrum look like to go from novice beginner all the way up to expert? [00:04:07] At what point in your career do you feel like you started to deviate from falling recipes? [00:07:41] What does it really mean to be a mentor or a mentee and anybody can become a mentor? [00:18:28] If you're going to approach somebody to be your mentor, then try to make it a positive sum game somehow. [00:21:30] How are you supposed to work with a mentor? [00:23:37] Tor has a dilemma related to cohort analysis and attribution modeling [00:32:20] Helping each other build up confidence in this crazy job search environment [00:36:06] What are some roles that that can help in getting your foot in the door before becoming a data scientist? [00:38:26] What are some interesting job titles you've seen in your search? [00:46:39] How do I ask the correct question? [00:50:38] When you meet people that are very skilled, they go directly into the complexity of the problems and they basically create so many problems. Nobody wants to listen anymore. [00:55:04] I'm consistently taking new classes and courses that I consistently keep meeting new things I don't know. How do you go about it? Is there no end there? We all go around sharing ideas for how to learn more efficiently. [01:04:52] The quest for a golden resource [01:11:24] Tips for coding round interviews [01:16:54] Do we need OOP in data science? [01:18:47] Should I go to grad school?

Dave started his career in 1995 at Equifax, and has since gone on to start two successful companies: Sigma Analytics in 1997 (which was acquired by Merkle) and AnalyticsIQ in 2006. AnalyticsIQ is a dynamic, fast-growing Marketing Data and Predictive Analytics company that is focused on providing innovative consumer data and analytics solutions. AnalyticsIQ is actively hiring, checkout the open positions here: https://analytics-iq.com/who-we-are/#careers Get your hands on a sample dataset which has 500 rows and 50 features, perfect for doing an EDA project. Or some unsupervised learning. Check it out here: http://bit.ly/3dJSG96 Connect with Dave: Twitter: https://twitter.com/analyticsiq LinkedIn: https://www.linkedin.com/in/davekellyaiq/ Website: https://analytics-iq.com/ Shoutout to Dave and the team for sponsoring this episode, it means a lot to be supported by a company with such an awesome culture and leader. If you're interested in having your organization highlighed in an episode, reach out to me at: theartistsofdatascience@gmail.com HIGHLIGHTS FROM THE SHOW [00:01:32] Guest introduction [00:03:07] We learn about where Dave’s from [00:04:58] What Dave thought his future would look like [00:06:08] We geek out over our mutual love of astronomy [00:07:03] Astronomy books that Dave recommends [00:07:42] What is database marketing and how did you become interested in it? [00:09:03] What is compiled data? [00:09:44] How did you start AnalyticsIQ? What was the opportunity you saw in the market and how did that spark the idea for starting this company? [00:10:51] What’s the mission of AnalyticsIQ? [00:12:13] How do you create these data sets? [00:14:56] What’s the change you want to see through your work at AnalyticsIQ? [00:16:58] How do you see data scientists working inside of larger companies benefit from using external data sources? [00:18:23] How AnalyticsIQ is using cognitive behavioral science to create their data sets [00:20:10] Working with survey data [00:21:44] How to structure questions so that people give valuable answers [00:23:09] What’s so unique about the PeopleCore dataset? [00:24:52] How big is this data set? [00:25:51] How having external and survey data can benefit businesses in a pandemic [00:26:52] Pandemic personas? [00:29:05] How do we make sure that Data is managed in a safe way so that we're protecting privacy? [00:30:57] How can we use data for good? [00:32:43] How can somebody who's armed with nothing but a laptop use data and analytics for good? [00:36:37] Some examples for how you can help your local community using your data skills [00:43:39] Do you have any advice or tips for anyone who's toying with the idea of entrepreneurship? [00:46:07] What do you see as some problems worth tackling that maybe an enterprising analytics professional can seize? [00:48:00] Dave’s philanthropic work [00:49:51] It is one hundred years in the future. What do you want to be remembered for? [00:50:50] The Random RoundSpecial Guest: Dave Kelly.

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 Register for Sunday Sessions here: http://bit.ly/comet-ml-oh 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 Chat transcript from the session: http://theartistsofdatascience.fireside.fm/articles/oh22-chat-transcript HIGHLIGHTS FROM THE SESSION [00:02:37] What probability distributions do you need to know as a data scientist? [00:06:07] What type of course should I take as a beginner in data science? [00:12:05] How much of software development and data science is bullshit [00:15:49] The myth of job security [00:20:34] How to build an intuition for data science [00:23:17] Thom Ives with some great wisdom [00:27:52] Book recommendation on thinking and learning [00:37:24] Build scrappy solutions [00:40:23] Use statistics to move KPIs [00:43:50] How to parse the text from an HTML blob [00:49:12] Thom changes his name to “What Mikiko said” [00:50:16] We talk about our biggest fails as data and analytics professionals [01:07:39] Juico’s webscraping question [01:11:43] The Data Community Content Creator’s AwardsSpecial Guests: Carlos Mercado, Greg Coquillo, Mikiko Bazeley, and Vin Vashishta.

Sadhna is the Vice President of Client Services at Darwin Research Group where she gets to work with a team of superhuman data scientists to provide advanced intelligence and in-depth strategic insights to health care executives. More interestingly though, she’s a Gelotologist - who specializes in studying the correlation between humor and intelligence. Connect with Sadhna Online: Website: http://sbokhiria.com/ LinkedIn: https://www.linkedin.com/in/sadhna-bokhiria-ed-d-52684553/ QUOTES [00:16:27] "Genuine laughter is definitely the best in terms of your wellness because it feels great, but your body really doesn't know the difference. So, even fake laughter has positive benefits for your body." [00:17:54] "I think people admire that. And I think people find something remarkable in that person who's not afraid to kind of take a chance and bet on themselves." [00:20:10] "If you live in the box, you don't know any better. Ignorance is bliss. But once you're outside of the box and you can see everything, it's like you never really want to go back inside the box because that's like a lesser state of existence." [00:29:23] "Failure is an inevitable part of their success. It's necessary for their growth. So, if we can take more of that into our lives and understand that you're either going to learn from it and grow and get back on stage and do better the next time; or you're just going to sink and stay in that space and and not really move forward." [00:36:24] "I think that as human beings, especially artists, especially people who demand perfection, such as myself, it's debilitating. You don't want to do it unless it's perfect. And that stops you from doing it because nothing is perfect. So, recognizing that sometimes progress is better than not doing anything right. So just breaking it down into those steps and saying, look, I'm going to do this and if it works out, it works out. And if it doesn't, I did it. It's that not having that regret." [00:42:53] "Data scientists are intimidating in their brilliance. Because, you know, if you're a Data scientist like you are like up there like. You're extraordinary. And it's a rock star kind of role when you read about the positions, and the companies, and the sheer power of data in itself in this day and age. So, I think maybe some advice for your listeners is: You guys are rock stars. There's hundreds of millions of people who would kill to be a data scientist, and you don't need to know everything." HIGHLIGHTS FROM THE SHOW [00:01:34] Guest introduction [00:02:53] We learn about where Sadhna grew up [00:06:10] We talk about identity [00:07:57] What Sadhna was like back in high school [00:09:11] The path that led Sadhna to where she is today [00:11:20] How Sadhna got so interested in studying comedians [00:16:03] The physiological benefits of laughter [00:16:45] The relationship between being humorous and intelligence [00:19:40] Can people “suffer from intelligence”? [00:22:49] How to develop your “ humor skills” [00:24:13] Are funny people more emotionally intelligent? And if so, why is that? [00:25:52] Does laughter help us improve our relationships? [00:26:52] The impact that always communicating through screens has on emotional intelligence, especially in the workplace [00:28:37] What can stand-up comedians teach us about problem solving? [00:32:15] What do you think makes a good leader? [00:35:31] Why you shouldn’t be afraid to share more of yourself and your story [00:37:49] Do we have to be in official leadership role to be a good leader or to show leadership? [00:40:18] How can we start allowing people to be the best version of themselves? [00:44:02] Do leaders have a better sense of humor? [00:45:17] What does it mean to “be authentic”? [00:47:51] Why is it more important that we keep it real in the first place now more than more than ever? [00:49:42] Can we cultivate authenticity as a trait? [00:51:47] Can we use authenticity to help us combat imposter syndrome? [00:54:06] It's one hundred years in the future, what do you want to be remembered for? [00:55:05] The Random RoundSpecial Guest: Sadhna Bokhiria.

Comet provides a self-hosted and cloud-based meta machine learning platform allowing data scientists and teams to track, compare, explain and optimize experiments and models. Backed by thousands of users and multiple Fortune 100 companies, Comet provides insights and data to build better, more accurate AI models while improving productivity, collaboration and visibility across teams. Register for future sessions here: http://bit.ly/comet-ml-oh Checkout Comet ML by visiting: https://www.comet.ml/ Or on Twitter: https://twitter.com/CometML On YouTube: https://www.youtube.com/channel/UCmN63HKvfXSCS-UwVwmK8Hw Connect with Ayodele LinkedIn: https://www.linkedin.com/in/ayodeleodubela/ Twitter: https://twitter.com/DataSciBae Check out her course on LinkedIn Learning: https://www.linkedin.com/learning/supervised-learning-essential-training/supervised-machine-learning-and-the-technology-boom [00:01:17] We talk about the madness of the data science interview process [00:02:29] Why are why are we making it so difficult for people to even get considered for an interview? [00:05:41] Could data science benefit from a series of exams and accreditations, much like actuaries have to do? [00:07:53] How does one prepare for these technical questions? [00:11:35] How long should you spend preparing for an interview? [00:12:58] What are considered medium/hard type of questions? [00:16:02] Am I expected to have an answer for everything? [00:20:46] How many projects should I have, and what should they be like? [00:24:25] How should I be allocating my time in the job search process? [00:25:17] Book recommendations [00:28:30] Notebooks or scripts? [00:30:53] How to explain your projects? [00:35:07] Mark talks about some stuff he’s doing at work around creating and defining metrics and KPIs [00:41:16] Tor jumps in with some sage advice [00:44:46] Measuring the monetary value of your efforts [00:50:10] How do you get managers buying into creating a data project? [00:54:21] Explaining the value of your passion projects in an interview [00:57:03] NLP question time

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 Register for Sunday Sessions here: http://bit.ly/comet-ml-oh 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 [00:00:09] We kick it off with a practice presentation and then questions from the audience. This is an excellent learning experience for everyone! [00:13:30] Audience questions start here. [00:26:04] Tribe member Eric Sims shares some awesome news with us [00:27:15] We learn a lot about cloud technologies through the lens of a web scraping project [00:38:50] Can a business person manage a fully developed Data science team? And what are the skills required for that? [00:41:30] In data science, there are two types of leadership [00:43:38] What’s the difference between strategic leadership and technical leadership? [00:49:13] Data science leadership at the executive level vs team lead level [00:58:55] Question about an NLP project [01:04:35] Product management, metrics, and KPIs [01:12:28] Now what foundation does it take to break into engineering from Data science besides technical skills, what are their skills are needed to survive in engineering. [01:23:13] How to “cold call” and network on LinkedInSpecial Guests: Greg Coquillo and Vin Vashishta.