Superdatascience

John David Ariansen joins me for an episode on the best practices for getting into data science consulting, the importance of understanding data science and analytics, and how you can network, even during a pandemic. In this episode you will learn: Coronavirus and how it will affect the way we work [3:06] John David’s consulting work [8:19] Why did John get into consulting? [13:17] Does John David’s age affect his clients? [25:03] John David’s podcast [34:59] The difference between data science and analytics [40:26] Creating space for opportunities [49:54] 3 top tips for getting a job in data science [54:28] Additional materials: www.superdatascience.com/361

In this episode, I’m exploring some topics in proper sleep habits to help you keep good sleep schedules. Additional materials: www.superdatascience.com/360

Emily Robinson breaks down her new book “Build a Career in Data Science” by sharing what skills she focuses on exploring, who the data science field is for, and how to tackle interviews and negotiations. In this episode you will learn: Long-distance networking [5:58] Emily’s book [9:38] Who is the field of data science for? [14:02] Should newcomers use Python or R? [23:34] Five company archetypes [28:36] Approaching data science interviews and negotiating [31:25] How do you actually get an interview? [48:08] Emily at DSGO 2020 [57:07] Emily’s final take-home message [58:52] Where to buy Emily’s book and SDS discount code [1:04:26] Additional materials: www.superdatascience.com/359

In this episode, I’m discussing my personal experience with discrimination during a trip at the start of the pandemic and how it elevated my understanding of racism and discrimination beyond just a cognitive level. Additional materials: www.superdatascience.com/358

Tracy Crossley, a Behavioral Relationship Expert, talks about how you can explore yourself during this difficult time. We also explored how different relationship dynamics can be tested during a forced lockdown and how to avoid dangerous emotional pitfalls. In this episode you will learn: What work does Tracy do? [5:50] Tracy’s training [8:20] Tracy’s view on the consequences of the pandemic [12:55] Ways to tackle emotions during lockdown [17:14] Final advice to those struggling during lockdown [1:00:11] Additional materials: www.superdatascience.com/357

Today, I’m helping you explore working remotely. Whether you’ve started doing this during the pandemic or you've been interested in and exploring remote-based jobs recently. I outline three advantages and three disadvantages to consider. Additional materials: www.superdatascience.com/356

DJ Patil talks about ethics in data science and the importance of data science communities working together to make sure data science is an accelerant of solutions for our children and our children’s children. In this episode you will learn: How does it feel to be the person who created data science as we know it now? [3:17] What data science is not [6:01] Ethics and data science development in different countries [10:00] What is the “biorevolution”? [16:02] The importance of data sharing [20:10] The current state of Chief Data Scientist of USA [24:07] LinkedIn Q&A [26:03] What to think about when you think about data science [44:08] Additional materials: www.superdatascience.com/355

Today I discuss a negative coefficient as a philosophical concept in problem-solving in your life. Do you make things worse by ignoring a problem or doing the wrong things to fix it? Additional materials: www.superdatascience.com/354

Brian T. O’Neill joins me for an insightful dive into how you can implement human-centric practices into your data work, whether you’re a consultant or individual contributor. There are ways and steps to workshop best practices in conversations with stakeholders. In this episode you will learn: Brian’s two lives [7:28] Brian’s human-first focal point [10:05] The process of Brian’s consulting work [17:07] How can an individual contributor be better at design thinking? [40:43] Walkthrough Brian’s course and seminar [54:37] Additional materials: www.superdatascience.com/353

Today, we’re diving into our fifth and final part of our history of data science series by looking into data science’s future through the eyes of five of the most influential people in our space and how they see the next few decades. Additional materials: www.superdatascience.com/352

Stratos Hadjioannou is a freshly hired data scientist who is self-taught and made the jump to visit DSGO. He talks about his learnings, putting himself in a data science ecosystem, and how to tackle interviews with little experience. In this episode you will learn: Where did Stratos start? [6:16] How to keep the momentum for learning [12:20] Stratos’s goals [19:35] Planning the steps to getting a data science job [23:01] Triad for successful interviews [32:47] Application process [34:53] Experiences from the first data science job [45:51] Additional materials: www.superdatascience.com/351

Today, we take some time to discuss the real mental and emotional toll social distancing can take during the coronavirus. How can we effectively tackle each other's needs during this period? Additional materials: www.superdatascience.com/350

Brad Klingenberg talks about the unique way Stitch Fix uses algorithms and human-in-the-loop AI to generate excellent customer experiences and pull ahead of other retailers in the space. In this episode you will learn: Working in Stitch Fix [5:18] How does Stitch Fix work? [11:29] Stitch Fix algorithms tour [20:14] Open positions in Stitch Fix [36:25] Stitch Fix takeaways for other companies [39:07] Humans + machines [44:19] Stitch Fix global expansion [47:34] Future of personalization [50:16] Brad’s advice to data scientists [55:33] Additional materials: www.superdatascience.com/349

In the penultimate episode of our history of data science series, we look at 2015 on and watch as data science goes from being about hard skills and coding to being about ethics and progress. Additional materials: www.superdatascience.com/348

Kerri Twigg talks with me about her work in helping professionals talk about themselves and tell stories about their passions and professional work to land ideal jobs and propel their career trajectory. In this episode you will learn: Kerri at DSGO 2019 [6:09] Who is Kerri Twigg? [8:00] A case study from DSGO 2019 [9:51] How do you build a career story? [18:30] Kerri’s book and practices [32:35] How to prepare for interviews [43:22] 3-Parts of a career story [56:53] Additional materials: www.superdatascience.com/347

In this FiveMinuteFriday we take a break from our series on the history of data science to discuss productivity and my top 5 hacks for getting more hours out of your day and week. Additional materials: www.superdatascience.com/346

I speak with Dan Shiebler who works as a machine learning engineer at Twitter Cortex and at the same time, is doing a Ph.D. on applying category theory in machine learning. We discuss his work at Twitter, the importance of academics, and the future of machine learning. In this episode you will learn: What is great about Twitter [5:31] Dan’s Ph.D. program [9:25] Dan’s work at Twitter [18:07] Dan at DSGO 2020 [35:16] LinkedIn Q&A [40:25] Dan’s advice [1:03:58] Additional materials: www.superdatascience.com/345

In the third of five episodes in this series, I journey through 2010 into 2015 to look at the boom of self-driving cars, the growth of data science as a profession, and the beginning of educational paths for future data scientists. Additional materials: www.superdatascience.com/344

I speak with Jose Quesada, founder and CEO of Data Science Retreat about the purpose of his program to help data scientists learn and find jobs through a three-month retreat and portfolio project. In this episode you will learn: Overview of Jose’s current projects [5:55] "What if I don’t have a tech background?" [09:58] How does it work? [11:51] Program structure [21:24] Tips for picking a portfolio project [26:45] The program’s next intake [1:03:06] Additional materials: www.superdatascience.com/343

In the second of five episodes in this series, I take a step into the early 2000s and the true boom of data science as a profession and philosophy of study, as well as look at some of science fiction’s failed hopes for data science by this time. Additional materials: www.superdatascience.com/342