Ten podcasts for data scientists to subscribe to
I’m an avid podcast listener. I listen to podcasts when I’m walking, driving, knitting, and even brushing my teeth! I have learned so much from listening to podcasts, and I’m constantly sending podcast episodes to friends that I think they would appreciate.
As you may imagine, I particularly love podcasts related to analytics and data science. They help me stay updated on industry trends, new tools, and introduce me to new voices. They’re also fun to listen to! For me, listening to them doesn’t feel like work, but I have applied learnings from them directly to my job, which has helped me stand out in my role. Also, I find that listening to podcasts makes me a better storyteller — something that is always important as a data scientist.
With the start of 2023, when many of us are considering our New Year’s resolutions or looking for a fresh start, here are 10 podcasts that I think every data professional would enjoy and could learn from, along with specific episodes from each to listen to. You can find these podcasts linked below, in this playlist, or wherever you listen to podcasts.
1. The Analytics Power Hour
Tim, Michael, Moe, and the occasional guest discuss analytics topics conversationally and sometimes with explicit language. They claim to be the top-rated explicit analytics podcast on Apple Podcasts! They always bring on awesome guests and take the time to ensure they bring in diverse voices. They actually count how many male and female guests they bring on, and make sure to do an annual “women’s day” episode with only female voices!
I have been an avid listener since 2019 when I saw Tim Wilson give a talk called “Getting Value from Data Science without Being a Data Scientist” that Felipe Archila told me about. Tim mentioned his podcast there and I’ve been listening to it ever since.
Tim, Michael, and Moe are also very active on the measure.chat community, and I’ve gotten to meet them before at MeasureCamp, the Digital Analytics Association OneConference, and The Marketing Analytics Summit (which this year is June 20–21, 2023, in Las Vegas, and at which I will be a speaker!)
All the episodes are great, and they have an extensive archive so you can search for topics that you want to learn more about and are relevant to you. Here are some episodes that I suggest in particular:
- #117 (Rebroadcast): What’s in a Job Title? Maybe the Data Shows with Maryam Jahanshah
This is my top-most-shared podcast episode. Maryam Janashahi talks about job descriptions with too many requirements, too disparate requirements, or that come with a higher job title than the role needs, and how this ends up turning off qualified candidates — and especially qualified female candidates. I reflected on how this has affected me personally in a talk that I gave at the Marketing Analytics Summit in 2022, and how there have been jobs that I haven’t applied for because of the title, despite meeting 95 percent of the job requirements. - #176: Analytics on the High Seas: Data at the Helm of an Aircraft Carrier with Capt. Paul Lanzilotta
A great episode where you get to learn about analytics in an organization you might have overlooked regarding its use of iterative analytics — the U.S. Navy. This podcast was particularly interesting to me because I used to work at Home Depot on the analytics team for the Merchandise Execution Team (MET), and I saw parallels between how the crew members on a ship function and how employees of a store function. - #148: Forecasting (of the Political Variety) with G. Elliott Morris
A fascinating episode that talks through the process and challenge of forecasting elections. It was also great to hear that D3 actually has applications after I struggled to learn it in CSE 6242 in the Georgia Tech Online MS in Analytics. - #126 (Rebroadcast): When the Data Contradicts Conventional Wisdom with Emily Oster
Emily Oster takes a data-driven approach to talk about COVID-19 precautions in school, parenting, and pregnancy. I have bought her books “Expecting Better” and “Cribsheet” for every friend I have who is starting a family. - A few more that I would recommend: #178: The Modern Dashboard Dilemma, #121: Onboarding the Analyst, #132: Reporting vs. Analysis , and #160: Data Reliability and Observability with Barr Moses.
2. Women in Analytics After Hours
People talk about analytics, and they just happen to be all women! It’s very new, so there are only a few episodes, but they are all amazing. A few that I will highlight:
- Episode 5 — AI for Wildlife Conservation and Imageomics with Dr. Tanya Berger-Wolf
Tanya Berger-Wolf talks about creating the terms “computation ecology” and “Imageomics,” the benefits and risks to democratizing data, and the value of being able to experience how the data is collected. You also get to hear about some amazing animals and her life changing trip to Kenya. - Episode 1 — The Vocabulary of Data and Analytics with Elizabeth Gilbert
Elizabeth Gilbert talks about why it’s important that we use words the way that they are intended, and how important it is to have clear definitions of terminology. - Episode 3 — Community-Taught Sports Analytics & R Education with Meghan Hall
Meghan Hall talks about how she got into sports analytics, how you can too, and the challenges of sports data. I just love listening to women crushing it in male-dominated fields within male-dominated industries.
3. Visible Women
Caroline Criado Perez talks through different ways that women are systemically excluded or hurt by data, and how we can help close the gender data gap. It will make you think a lot about the types of data you collect and the unconscious biases that you may have.
I encourage every woman, every female ally, and every data professional to read Invisible Women and subscribe to the Invisible Women Newsletter. It will really change how you view the world. For example, every day that I sit at my desk, I think about how my desk chair is clearly designed for men, since I cannot sit with my feet flat against the floor as recommended. And, I realized that my master’s hood instructions were designed for men despite the fact that 60 percent of master’s degree graduates are women!
Here are a few episodes that I recommend in particular:
- Episode 6: Privacy versus the gender data gap
The gender data gap is created by the fact that we collect less data on women, and the data that we do collect is often not sex disaggregated, so we cannot determine negative outcomes that predominately affect women. For example, doctors misdiagnose heart attacks in women because we don’t tend to involve women in the medical studies where these symptoms are documented. In this episode, Caroline discusses the privacy issues that may come with her life mission of closing the gender data gap, and how it could possibly harm women. - Episode 2: Can playgrounds be sexist?
An amazing episode that shows how the design of systems can have an impact on how they are used. This could open other questions like “can offices be sexist?” or “Are pianos sexist?” - Episode 4: Deadly injustice — why cars aren’t safe for women
Women are more likely to be injured or die in car accidents because the only crash test dummies used are designed to emulate male bodies. This episode walks through the safety statistics, the history of crash testing for cars, and what actions you can take to advocate for female crash test dummies. Women are not just tiny men!
4. Freakonomics MD
Dr. Bapu Jena, an economist and Harvard physician, talks about a study at the intersection of economics and healthcare.
What I think any data professional will gain from listening to this podcast is a greater appreciation for experimentation, a deeper understanding of the differences between and limitations of natural experiments and randomized controlled trials, and learn why it is so challenging to get to “causal” especially in industries where it is infeasible, illegal, or unethical to knowingly withhold treatment from a control group.
A few of my favorite episodes are:
- COVID and the “Birthday Effect”
This was the first episode of Freakonomics MD that I listened to because it was played on the Freakonomics feed, and I just fell in love with it. I love how Bapu was able to construct a natural experiment using the fact that birthdays are randomly distributed. And even more, I love the fact that I learned about “falsification tests,” or creating fake random assignments (in this case birthdays) to confirm that the assignment actually was correlated to the result instead of being a fault in the analysis. It made me remember a previous role in which I was trying to find the impact that cleaning a shelf in a store had on store revenue and I was using the “random” cleaning schedule as a natural experiment. I have since left this role, but I sent my former manager this podcast episode and told him to double check my analysis through a falsification test! - A Shave, a Haircut, and a Blood Pressure Test (Update)
This episode walks through the design (and impact) of a randomized controlled trial (RCT). This particular RCT involved putting either a blood pressure testing machine or a blood pressure testing machine and a pharmacist who could prescribe blood pressure medication at barber shops in predominantly Black neighborhoods because hypertension disproportionally affects Black men. - How Does Retirement Affect Your Brain?
This episode has another clever random experiment. But what I love about this episode so much is the motivation behind it. Bapu started looking into how retirement affects one’s brain because his dad was looking to retire, and Bapu was worried about him. It shows that any conversation that you have could spark the idea for an analysis!
5. Freakonomics Radio
Freakonomics is the original Freakonomics podcast, inspired by the Freakonomics books. Host Stephen Dubner explores “the hidden side of everything” by applying his economist lens to just about anything.
- Will Work-from-Home Work Forever?
This episode is mostly pro-remote work. They argue that remote flexibility reverses the “brain-drain,” increases productivity, and increases diversity by allowing people like military and diplomatic spouses to remain in the workforce. They also talk about the importance of in-person and spontaneous interactions, but how randomly engineered virtual water coolers and scheduled in-person trips can also be effective at building relationships. This episode evaluates both random experiments and RCTs. If you’re interested in the topic, Planet Money’s The Indicator has a great episode about how remote work affects local economies, and the BBC has an amazing article about how remote work might affect diversity negatively. - Abortion and Crime, Revisited (Update)
Stephen Dubner is joined by his co-author Steven Levitt to discuss Levitt’s controversial research that found that access to abortion could reduce crime. This episode discusses his research, the reception, the controversies, follow up analysis, and the history of abortions in the United States. - Should Public Transit Be Free?
This is packed with real world experiments, differences in definitions of “cost” (such as time versus money), and concepts like equilibrium and elasticity. It’s a great thought experiment on why experiment results do not always pan out as expected when they are fully rolled out. - Why Do Most Ideas Fail to Scale?
Jon List, author of The Voltage Effect, talks through reasons why ideas (like free public transit mentioned above) might fail to scale. This is a must listen for anyone designing an experiment without random sampling. It makes me rethink a lot of experiments that I have seen where leaders manually select stores to be in the test population, confounding the results. - Why Did You Marry That Person?
A great episode exploring the natural experiment of love and the marriage market after Queen Victoria canceled the Season (the bi-annual dating event that the show Bridgeton is based on) three years in a row, and how one might measure “love.” - Did Domestic Violence Really Spike During the Pandemic?
An episode that tries to evaluate domestic violence trends around the pandemic, which notes how other behaviors during the pandemics (such as more people staying home and differing police priorities) might affect how the data is collected. It calls into question how trustworthy data can be, especially data during major events or natural experiments.
Because of Freakonomics Radio and Freakonomics MD, I’m always thinking about new natural experiments I could find to analyze, and best practices when designing RCTs.
6. The Data Engineering Podcast
This podcast is a little more technical, and like the title suggests, focuses more on data engineering. Data engineering is the backbone of any data science or analytics work, so it’s still important to keep up to date on any new trends in the industry.
I listen to this one only when a title or guest catches my eye, but here are a few that I have listened to recently:
- A Reflection On Data Observability As It Reaches Broader Adoption
I’m a big fan of Barr Moses, Monte Carlo, and the idea of data observability. Barr was just named a Top 100 Female Founder by Inc Magazine! You can also listen to Barr on the The Analytics Power Hour Episode #160. - Alumni Of AirBnB’s Early Years Reflect On What They Learned About Building Data Driven Organizations
It was really interesting to hear all of the directions that these data leaders took, and how they each applied their learnings from AirBnB.
7. DataFramed podcast from DataCamp
This is another podcast that I listen to only when the title or guest catches my attention, but I am always so impressed by the conversations when I do listen to them, and think to myself “why don’t I listen to this podcast more often?”
Here is the episode that I just can’t stop thinking about, have sent to three people in the last month, and is on my 5 Exceptional Podcast Episodes to Listen to — Volume 2
- The Rise of Hybrid Jobs & the Future of Data Skills
Matt Sigelman, chairman of Lightcast (formerly Emsi Burning Glass) and president of The Burning Glass Institute, talks about analyses they did on the workforce based on job postings and job requirements that they have collected over the years. Matt talks about the rise of hybrid-skilled roles (roles that require skills from two or more different job families like marketing and analytics), skill replacement (roles where skills that were needed 10 years ago are no longer needed, but new roles with new skills are, such as data scientists), and demand for different job titles and skillsets.
8. Not So Standard Deviations
Hilary Parker has a Ph.D. in biostatistics and has worked in data science at Stitch Fix, Etsy, the 2020 Biden Presidential Campaign, is the former CTO at Indyx (a wardrobe concierge startup), and currently does consulting. Hilary and Roger, a Statistics and Data Sciences professor, are supposed to talk about data science, but often just talk about random things. It’s always fun to listen to, but sometimes you don’t really learn about data science.
- 137 — Getting to Right
This is the episode that got me to start listening to the podcast. Hilary and Roger discuss how people might determine whether data analyses are “right” and how we can incentivize people to quality assure (QA) other’s code. - 147 — Data Science TPS Reports
On a similar vein as the episode above, Hilary and Roger discuss the pros and cons of an analytics rubric or checklist, and what would make a good one. - 139 — Eliciting Chocolate
I like this episode because Hilary is as into advocating for The Good Chocolate as I am into advocating for brands that I love (such as fairlife milk and shopping on thredup for secondhand clothes to save money and help the environment) and brands that I have worked for (like Capital One, Home Depot, and, of course, Microsoft), and also talks about the analytics she wishes she could do at all of the companies that she loves.
9. Grit from Kleiner Perkins
This podcast is more about business than analytics, but it is so valuable for data professionals to understand how businesses works holistically to make the greatest impact. Joubin Mirzadegan is an amazing host who brings on unbelievable guests and creates compelling, inspiring, and engaging conversations. I recommend Grit over other business-focused podcasts because Joubin typically brings in executives who accelerate business (usually CROs and CMOs), and who are typically the executives who rely on analytics to drive decision-making. It focuses more on growth and decision-making more than other business podcasts that I’ve heard.
Some of my favorite episodes are:
- AOL Founder & CEO Revolution, Steve Case: The Rise of the Rest
This episode was so interesting as it reflected on how much the world has changed in the last 30 years. We learn about AOL’s early market motions, how AOL became the top internet provider, AOL’s relationships with Apple and Time Warner, how the world used to view young CEOs, and how Steve Case is investing in the future through Revolution. - CMO Riot Games, Jason Bunge: Change Is Inevitable, Get Used To It
I don’t really get the appeal of video games outside of maybe Animal Crossing or Pokémon, so it was great to learn about the business behind gaming and gaming events, how the industry has evolved, and why passion is more important than audience size. - Chief Freemium Business Officer at Spotify, Alex Norstrom: The Power of Setting Impossible Goals
As someone who totally fell for the “Three months of Spotify for only $0.99” marketing while I was in college, it was fascinating to hear how effective and revolutionary that marketing play was, and the amount of testing time frames and prices that went into that campaign. Alex also discusses how Spotify entered the podcast space, which is especially relevant now as Spotify enters Spotify Audiobooks. - CMO Airtable, Archana Agrawal: Success Is Not a Formula
It was amazing to hear about Archana’s background: She moved to India from Liberia to escape a civil war, her dad was her roommate in grad school, and she cold-emailed her way to a job at her dream company. Listening to this podcast got me interested in Airtable as a product, and it’s still on my personal backlog to put all my podcast, article, and book recommendations into an Airtable workspace to create interactive tables and dashboards to filter my recommendations.
10. Technical Marketing Handbook
Simo Ahava explains technical topics that everyone working in digital marketing, digital analytics, advertising, and more should know about. What I like about this podcast is that it isn’t just aimed at technical people and can help you speak to your non-technical stakeholders about these technical concepts.
Some episodes that I like are:
- TMH #9: Experimentation with Matt Gershoff
In particular, I really like how Matt Gershoff explains p-values using an example of waiting for a train in a foreign city. - TMH #12: Missing Motivation with Simo Ahava & TMH #13: Take Care Of Your Expertise with Simo Ahava
Simo shares his motivation slump, and ways to try to stay motivated. I feel like this topic is so important, especially now.
Honorable mentions
I wanted to add a few more podcasts that I also love, but aren’t quite “data focused” enough to make the list:
- How I Built This with Guy Raz
This podcast talks with entrepreneurs to learn how they built their brand. This podcast is similar to Grit, but because Grit focuses more on revenue, growth, and decision-making, I feel that it’s more relevant to data professionals. However, I always love How I Built This and think it’s great! - 99% Invisible
99% Invisible is about hidden design in everyday life. It is not often about data and technology, but when it is, it is great. In particular, Pandemic Tracking and the Future of Data, Murder Most Fowl, The Future of the Final Mile, and Alphabetical Order. - A Matter of Degrees — stories for the climate curious
I find that most science podcasts are data focused and are more powerful when they are. Some great data-focused episodes of this podcast are How Gender Equality Can Save the Planet — The Earth benefits when women lead on climate action and Season 2, Episode 5: A Farming Solution for a Hotter, Less Stable World. - Planet Money and The Indicator from Planet Money
These podcasts are economics based, but again, it’s hard to talk about the economy without using data!
Some great data related Planet Money episodes are A new way to pay for college, Micro-Face: The Musical, Little house on the Blockchain, and The tale of the onion king.
Some great data-related Indicator episodes are The California Effect, The surprising economics of digital lending, The secret to upward mobility: Friends, and What is a “household”?
Now that I’ve shared my favorites with you, I would love to know:
- Are there any podcasts that you think I missed?
- Did you subscribe to any new podcasts because of this article?
Please comment below to let me know!
Also, if you enjoyed this article, follow me on Medium! I started a blog series to share my five favorite podcast episodes every month or so, and because I’m a data scientist and listen to the above data-related podcasts, they will likely be data related. You can see my first one here: Five Exceptional Podcasts Episodes to Listen to.
Riesling Walker is on LinkedIn.
