Superdatascience

Michael Galarnyk joins to tackle your questions on data science job hunting and data science education.  In this episode you will learn: Who is Michael Galarnyk? [3:48] Tools and skills to know [11:52] Building and sharing a portfolio [26:21] Advantages of online and in-person education [37:42] Teaching data science to younger students [43:55] Necessary soft skills to be a successful data scientist [51:31] Additional materials: www.superdatascience.com/401

In this anniversary episode, we discuss the importance of knowing why you do data science and how your skills may one day impact the world as challenges arise. Additional materials: www.superdatascience.com/400

Monica Royal joins us to discuss her journey from consumer to contributor in the data science community and how sharing your work and exploring networking can help you on your journey. In this episode you will learn: Monica’s activity in the data science community [5:17] The biggest takeaways from Monica’s 100 Days of Learnings [11:00] Techniques for productivity and continued learning [16:03] Monica’s interest in the SDS podcast and keeping up to date in data science [33:01] The DataScienceGO Virtual experience [35:51] Strategic thinking [38:38] Monica’s parting inspirational thoughts [41:01] Additional materials: www.superdatascience.com/399

In this episode, I discuss a very important topic on the stages and symptoms of burnout and how to tackle them at each point to avoid irreparable damage. Additional materials: www.superdatascience.com/398

We chatted with data science influencer, educator, and principal data scientist Kirk Borne about his philosophy and work in spreading data science literacy across fields and industries through his frameworks. In this episode you will learn: Live vs. virtual events [4:20] Who is Kirk Borne? [7:13] Big data’s evolution and the emergence of small data [11:17] The fourth industrial revolution and the future [22:00] How has the data science education space changed in 14 years? [33:44] Four types of data discovery [38:00] The broad categories of AI you should pursue [50:44] 5 levels of analytics maturity [53:50] LinkedIn Q&A [1:05:00] Hiring at Booz Allen [1:15:18] Additional materials: www.superdatascience.com/397

In this episode, I share a series of great tips, plus a bonus tip for getting your application further along in the hiring process and getting the job. Additional materials: www.superdatascience.com/396

Cole Nussbaumer Knaflic talks about her influential book Storytelling with Data and shares some best practices for conveying meaning from your visualizations. In this episode you will learn: Cole’s business Storytelling With Data [4:04] How did Cole get into this space? [7:24] When did Cole start writing the book? [15:33] Top 3 tips from the book [22:44] How to structure a good story [35:17] Communicating in-person vs. virtually [41:37] Cole’s upcoming workshops [43:50] LinkedIn Q&A [48:57] Cole’s advice on preparing for the future in the field [1:05:22] Additional materials: www.superdatascience.com/395

In this episode, I discuss the power of teaching what you learn to help you retain the highest amount of the information you are learning. Additional materials: www.superdatascience.com/394

John Peach joins to discuss his passion for bringing more scientific approaches to the data science field, making it smarter and more efficient. In this episode you will learn: John’s move from Canada to the US [3:37] John’s new position at Oracle [8:31] Data Science Workflows [9:34] John’s solution to data science workflow exploration [12:06] John’s data science design thinking framework [21:20] Case study [34:21] Literate statistical programming [43:12] R or Python? [51:55] Data unit testing [53:28] What drives John? [1:00:56] Additional materials: www.superdatascience.com/393

In this episode, I describe my morning ritual and discuss the importance of setting up a morning ritual for yourself. Additional materials: www.superdatascience.com/392

John Elder joins for an amazing podcast to share his data science "campfire tales" spanning over 20 years of his career in the industry. It will definitely help you in your work to incorporate some of the best principles. In this episode you will learn: John’s first bungee jump [4:01] Calculus and newer approaches [14:01] Elder Research [21:11] Domain knowledge advice [25:26] The importance of instincts [41:52] Ensembles and simplicity [59:33] John’s opinions on neural nets [1:10:49] Target shuffling method [1:17:27] What does the future of data science hold? [1:39:53] Additional materials: www.superdatascience.com/391

In this episode, I share a tip I came across this week about avoiding conflict in interpersonal relationships. Additional materials: www.superdatascience.com/390

Josh Hortaleza discusses how he’s become a juggernaut of an aspiring data scientist and powered through networking and internships to reach his goals in the field. In this episode you will learn: How did Kirill and Josh meet [8:26] Who is Josh? [12:42] Josh’s first internships [17:07] Being “good enough” and the luck factor [34:51] Josh’s goal [40:55] Genuine networking [43:08] Additional materials: www.superdatascience.com/389

In this episode, I share an awesome tip for anyone at any level around recruitment and headhunters. Additional materials: www.superdatascience.com/388

Lillian Pierson discusses her work on data leadership and how any data scientist can become a data leader in their organization or community. In this episode you will learn: Who is Lillian Pierson? [3:27] Winning With Data [6:08] Four superpowers of great data leaders [11:53] Benefits of developing these skills [17:27] Examples of quick win challenges in Winning With Data [19:34] Impact of COVID-19 [22:23] Where is the industry going? [28:26] Additional materials: www.superdatascience.com/387

Today, I explain cohort analysis and how this can be used for conversion metrics and tracking the customer journey. Additional materials: www.superdatascience.com/386

T. Scott Clendaniel joins to discuss advanced topics in data science and his forecasts for the future in this field. He also talks about the importance of soft skills for data scientists. In this episode you will learn: Who is Scott Clendaniel? [6:57] Scott’s role at Franklin Templeton [10:24] LinkedIn advanced Q&A [13:29] Tools that Scott uses the most [26:57] Target mean encoding technique [30:35] LinkedIn Q&A on models [33:11] LinkedIn Q&A on soft skills [54:04] LinkedIn Q&A on forecasts for the future [01:00:19] Hub and spoke model in Data Science Management [01:08:32] Scott’s advice for advanced data scientists [01:10:12] Additional materials: www.superdatascience.com/385

Today, I discuss best practices for data visualization and how to build on what we learned about cognitive load. Additional materials: www.superdatascience.com/384

Sean Casey joins to discuss his data science journey and how he’s used online courses, secondary resources, and the wider network to help his journey to a data visualization professional. In this episode you will learn: How Sean and Kirill met at DSGO Virtual [4:25] Sean’s experience at the virtual event [7:32] Sean’s journey [10:06] Do you need the credibility of a degree? [22:01] Sean’s supplemental readings [24:33] What can others do to replicate Sean’s success? [39:18] Sean’s advice for others just starting [50:15] Additional materials: www.superdatascience.com/383

Today, I discussed the types of cognitive load and how to best utilize them when imparting information through data. Additional materials: www.superdatascience.com/382