All Episodes


Executive Panel: How Can Data Science, ML, and AI Best Support Executive Goals

Today is a special episode. We welcome three executive guests from different organizations to share their experiences and insights about how data science can best support executive goals. Ginette Methot: I’m Ginette Curtis Seare: And I’m Curtis Ginette: And you are listening to Data Crunch Curtis: A podcast about how applied data science, machine learning and artificial intelligence are changing the world. Ginette: Data Crunch is produced by the Data

The Biggest Pitfalls of New Analytical Initiatives

Our guest Andrzej Wolosewicz has had years of experience helping companies define and build machine learning and analytical solutions that have a measurable impact on the business, and he shares with us his experience and expertise. He shares with us the biggest pitfalls he sees companies fall into over an over as they try to implement these initiatives. The problem was there was a lot of activity every month that

Digital Credentials and Machine Learning Aim to Change How You Hire

Today we’re going to see how a clever idea and the skillful use of data is starting to disrupt how people get credentials. The use case here has the potential to remove gender and racial bias in the hiring process, help companies understand specific talent gaps in their workforce, and help learners find lucrative educational pathways they can take.

How to Win Hearts and Minds as a Data Leader

Joe Kleinhenz talks about his journey from starting out in data all the way to becoming a leader in one of the largest insurance organizations in the United States. We’ll learn about the importance of staying on top of technology, how to win hearts and minds of nontechnical folks, centralized versus decentralized team, pros and cons, how to hold effective conversations with stakeholders and how to go from individual contributor

Building Data Products that Work in the Health and Wellness Industry

Our guest today holds a PhD in organizational psychology and has been working on data products in the health and wellness space for over a decade. We cover a lot of ground in this interview: how to create data products that work, how to avoid the unexpected consequences of poorly designed data interventions, and the importance of ethnographic thinking in data science. We'll also talk about reducing friction in data collection, the coaching data product model, and surprising things we can learn when people's routine's are broken. From today's episode, you'll come away with a better understanding of how to build contextually relevant data products that make a difference in people's lives.

The Road to a Data-Driven Culture in Your Organization

How do you whittle the murky business of creating a data-driven culture down to a proven process? Today we talk to a guest who has done this time and time again, helping companies transform their operations. He points out the small nuances and details about the process, like questions to ask to start on the right foot, critical feedback loops to put in place along the way, and how to

Statistics Done Wrong—A Woeful Podcast Episode

Beginning: Statistics are misused and abused, sometimes even unintentionally, in both scientific and business settings. Alex Reinhart, author of the book “Statistics Done Wrong: The Woefully Complete Guide” talks about the most common errors people make when trying to figure things out using statistics, and what happens as a result. He shares practical insights into how both scientists and business analysts can make sure their statistical tests have high enough power,

Getting into Data Science

What does it take to become a data scientist? We speak with three people who have become data scientists in the last three years and find out what it takes, in their opinions, to land a data science job and to be prepared for a career in the field. Curtis: We’ve talked a lot in our recent episodes about all the interesting things you can do with data science, and

Automated Machine Learning with TransmogrifAI

Would you rather take a year to develop a proprietary algorithm for your company that has an accuracy of 95% or use an open source platform that takes a day to develop an algorithm that has nearly the same accuracy? In most business cases, you'd choose the latter. In this episode, we talk to Till Bergmann who works on a team that developed TransmogriAI, an open source project that helps you build models quickly.

The Data Scientist’s Journey with Nic Ryan

What does it take to become a data scientist? Nic Ryan has been in the field for over a decade and answered thousands of questions from people looking to get into the field. In this episode, he talks about his journey into data science and his experiencing mentoring aspiring data scientists, giving advice to both beginners and seasoned professionals. Nic Ryan: I think there’s sometimes a problem in data science