17 Data Science Podcasts to Listen to in 2022 (2022)

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17 Data Science Podcasts to Listen to in 2022

Written by Coursera • Updated on

Find your next data science listen from this list of current podcasts.

17 Data Science Podcasts to Listen to in 2022 (1)

Whether you’re looking for a way to build up your data science vocabulary, keep up with the latest developments in the field, learn new data skills, or even get advice on getting your first data science job, there’s a podcast for that.

Listening to some of these 20 podcasts can be a great way to improve yourself as a data professional, whether you’re just starting out or are already a seasoned pro. The best part? You can squeeze in some listening when you’re cleaning the house, grocery shopping, exercising, or otherwise on the go.

We’ve divided this list into a few broad categories to make it easier for you to find what you’re looking for. At the time of writing, these podcasts are all active and in production.

Read more: What Is a Data Scientist? Salary, Skills, and How to Become One

Podcasts to get an overview of data science

Whether your interest in data science is academic or professional, these podcasts offer a broad, high-level overview of a range of data topics. This is a good place to start if you’re new to data science or if you want a little of everything in your podcast listening.

1. Analytics Power Hour

Episode duration: About an hour

Frequency: Biweekly

The premise of this podcast is that the best, most informative discussions happen around drinks after an event, like a conference or show. Co-hosts Michael Helbling, Tim Wilson, and Moe Kiss share their thoughts on a different data topic each week, from the psychology of data analytics to making statistics more accessible.

Recommended episode: The Curiosity of the Analyst with Dr. Debbie Berebichez

2. Data Skeptic

Episode duration: 30 to 40 minutes

Frequency: Weekly

This popular data science podcast, hosted by Kyle Polich, covers a wide range of topics, including machine learning and artificial intelligence, and statistics. The library of some 370 episodes and counting alternates between mini episodes that cover high-level topics and longer, more in-depth interviews with practicing data scientists.

Recommended episode: Data Science Hiring Processes

(Video) Science-Based Tools for Increasing Happiness | Huberman Lab Podcast #98

3. DataFramed

Episode duration: 45 minutes to an hour

Frequency: Biweekly

In this podcast from DataCamp, host Adel Nehme interviews data leaders working in both industry and academia about all things data science—its past, present, and future, as well as the types of problems data science can solve. Older episodes were hosted by data scientist and writer Hugo Bowne-Anderson.

Recommended episode: The Past and Present of Data Science (with Sergey Fogelson)

4. Women in Data Science

Episode duration: 30 to 40 minutes

Frequency: Monthly

Professor Margot Gerritsen from Stanford University hosts a series of conversations with leading women in the data science field. Listening gives you an overview of how data science is applied across a range of industries, from music streaming to health care, along with plenty of career advice learned from experience.

Recommended episode: Lillian Carrasquillo | Using Human-Centric Data Science at Spotify

5. Lex Fridman Podcast

Episode duration: Two to five hours

Frequency: Twice weekly

This podcast, once called “The AI Podcast”, is no longer all about data science, but it does offer a broader perspective of data science and how it fits into the bigger picture of philosophy, history, health, and technology. Lex Fridman interviews luminaries from various industries—figures like Elon Musk (CEO of Tesla), Vitalik Buterin (co-founder of Ethereal), and Saagar Enjeti (political correspondent).

Recommended episode: Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot

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17 Data Science Podcasts to Listen to in 2022 (2)

Podcasts for career advice

If you’re thinking about starting a career as a data analyst or data scientist, or if you’re working toward advancing in your current role, these podcasts are for you. While they’re not all exclusively about job tips, they do lean toward the pragmatic.

6. SuperDataScience

Episode duration: Five minutes (mini episodes) to an hour (full episodes)

Frequency: Twice weekly

This lighthearted podcast features conversations around the tools, techniques, and data-driven processes involved in real-world data science. Learn more about the history of data, knowledge graphs, or time series analysis, or get job ready with episodes focused on resume tips and myths about pursuing a data science career.

Recommended episode: How to Thrive as an Early-Career Data Scientist

7. Data Futurology

Episode duration: 30 to 45 minutes

Frequency: Weekly

Data science executive Felipe Flores hosts this podcast, where he interviews some of the world’s leading data practitioners. While the show focuses on the leadership side of artificial intelligence (AI), the content often includes useful bits of advice for how to get started—and excel—in the wide world of data.

(Video) Women Rock-IT: What's So Exciting About Data Science?

Recommended episode: Machine Learning: Getting the Skills Needed to Work as a Data Scientist or Machine Learning Engineer with Alexey Grigorev

8. The Artists of Data Science

Episode duration: An hour to 90 minutes

Frequency: Weekly (or more)

This podcast focuses exclusively on self-development for data scientists. Each episode comes full of advice on how to develop professionally, stay informed, and practice good data ethics. Episodes are divided between interviews and “happy hours” where listeners can ask questions on anything related to data science.

Recommended episode: Your Job Doesn't Define YOU | Eleanor Tweddell

Podcasts for data science news and trends

No matter where you are in your data science career, it’s always a good idea to stay current with the latest in data and how it’s impacting the world. Subscribe to these podcasts to stay in the know.

9. Not So Standard Deviations

Episode duration: 20 minutes to an hour+

Frequency: Two to three per month

Roger Peng (professor of biostatistics at Johns Hopkins Bloomberg School of Public Health) and Hilary Parker (data scientist at Stitch Fix) co-host this discussion of industry news that weaves in their own personal experiences working with data.

Recommended episode: Data Gunslingers

Podcasts about machine learning and AI

It’s hard to talk about data science without some mention of machine learning and AI. If you’d like to learn more about these critical fields of data science, take a listen to one of these podcasts.

10. Data Science at Home

Episode duration: 20 to 40 minutes

Frequency: Once or twice a week

In Data Science at Home, Dr. Francesco Gadaleta discusses topics in machine learning, artificial intelligence, and algorithms and interviews top minds in the field of AI. Past episodes have covered how to work with unbalanced data, what true machine intelligence might look like, and why we don’t get paid for our data, even though it’s worth thousands of dollars each year.

Recommended episode: True Machine Intelligence just like the human brain

11. The TWIML AI Podcast

Episode duration: 45 minutes to an hour

Frequency: Twice weekly

During this podcast, formerly This Week in Machine Learning & Artificial Intelligence, analyst Sam Charrington interviews researchers, data scientists, engineers, and IT leaders on a broad range of topics related to machine learning and AI. Learn more about the latest in autonomous driving, haptic intelligence, and how AI might be used to map the human immune system.

Recommended episode: Machine Learning for Equitable Healthcare Outcomes with Irene Chen

12. Gradient Dissent

Episode duration: 45 minutes to an hour

Frequency: Twice monthly

This machine learning podcast gives a behind-the-scenes look at how leaders across a variety of industries are using machine and deep learning models to solve real-world problems. Guests on the show have included Wojciech Zaremba (co-founder of OpenAI), Sean Taylor (data scientist at Lyft), and Chris Mattmann (Chief Technology and Innovation Officer at the NASA Jet Propulsion Laboratory).

Recommended episode: Alyssa Simpson Rochwerger on responsible machine learning in the real world

13. In Machines We Trust

Episode duration: 20 to 30 minutes

Frequency: Biweekly

This show bills itself as “a podcast about the automation of everything,” and it examines the impact of AI on our daily lives. Jennifer Strong with the MIT Technology Review guides listeners through discussions on the ways we entrust technology with some of our most sensitive decisions.

Recommended episode: Hired by an algorithm

Podcasts on specific data topics

Podcasts are a great way to take a deep dive into a particular topic in the data world, whether to learn a new skill or pick up some tips on a data task you perform regularly. Each of these podcasts focuses on a specific element of data science.

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14. More or Less: Behind the Stats

Episode duration: 8 minutes

Frequency: Weekly

This podcast from Tim Harford and the BBC helps make sense of statistics through short and snappy episodes. Topics are wide ranging—everything from how data has helped double life expectancy to calculating how many swimming pools of vaccine we’ll need to give everyone on the planet a dose.

Recommended episode: Delta cases, blue tits and that one-in-two cancer claim

15.Talk Python to Me

Episode duration: An hour to 75 minutes

Frequency: Weekly

Python’s versatility as a programming language is on full display in this podcast, which has already recorded more than 320 episodes about Python and related technologies. The show, hosted by Michael Kennedy, splits its time between how Python is applied by data scientists, software developers, and even the casual hobbyist.

Recommended episode: Python for Astronomy with Dr. Becky

16. The Data Engineering Podcast

Episode duration: 40 minutes to an hour

Frequency: Twice weekly

If you’re interested in the specialized role of data engineer, this podcast is for you. The show focuses on the tools and techniques associated with data engineering, as well as the difficulties engineers might face when managing workflow, automation, and data manipulation. This one’s full of insightful advice.

Recommended episode: Moving Machine Learning Into The Data Pipeline at Cherre

17. Data Viz Today

Episode duration: 30 minutes to an hour

Frequency: Monthly

Data is at its most powerful when it tells a compelling story, and visualizations can help achieve that end. In this podcast, data visualization designer Alli Torban shares the latest methods and tools through her own work and interviews with other top data designers.

Recommended episode: How to Turn Data Into an Experience

Archived podcasts: Gone but not forgotten

These podcasts are no longer (or infrequently) producing episodes, but as industry favorites, we thought they were still worth mentioning. If you’re looking for your next data science listen, go ahead and dig into the archives of these longstanding favorites.

1. Partially Derivative

2. O'Reilly Data Show Podcast

3. Linear Digressions

4. Talking Machines

5. Data Stories

6. Data Science Imposters

(Video) PBS NewsHour full episode, Nov. 23, 2022

7. The Banana Data Podcast

8. Learning Machines 101

17 Data Science Podcasts to Listen to in 2022 (3)

Get started in data science

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FAQs

Should I learn data science in 2022? ›

Even in 2022, data science is without a doubt one of the sexiest tech fields to get into, with six-figure salaries, low unemployment rates, and the ability to work from anywhere in the world.

Who is the No 1 data scientist? ›

1. Randy Lao. If you're an aspiring data scientist, this is the one data scientist you need to follow. Check out his website wherein he has shared all the useful data science and machine learning resources FREE of cost!

Why so many data scientists are leaving? ›

Professionals who land such roles become unsatisfied in their positions leading to high resignation rates. When employers gloss over data scientist positions to make them captivating for top talent, these employees eventually become unhappy and leave the company for better opportunities.

What's next for data scientist? ›

The future of Data Science jobs will look like the middleman who can communicate with computers and humans. AI and Machine learning are just tools that a data scientist uses to deal with big data. Data Science and Machine learning go hand in hand.

Is 40 too old to become a data scientist? ›

So despite industry ageism, a recent study by Zippia showed that the average age of data analysts in the U.S. is 43 years old. This takes us back to our titular question: are you too old to start a new career in data analytics? The short answer, in our opinion, is no.

Can a 40 year old learn data science? ›

You are not late to learn data science. It is not an easy task to learn data science and find your first job. It takes time, effort, and dedication. You may have to spend months to obtain the basic skills.

Who is the richest data scientist? ›

Alexander Karp – Palantir Technologies – $1.6 billion.

What is the highest salary paid to a data scientist? ›

How much does a Top Data Scientist make in the United States? The average Top Data Scientist salary in the United States is $263,742 as of October 27, 2022, but the range typically falls between $239,003 and $298,462.

Who is the youngest data scientist? ›

Born and brought up in the UAE, Veer started learning coding at 8. Clevered provided him with an online internship at the University of Oxford. At the age of 11, he developed a passion to innovate and solve real-world problems. The Junior Data Scientist program was initially assigned for 14+ years.

Is data scientist a 9 to 5 job? ›

Great Exposure to Different Data Science Projects on Different Platforms. What would you wish for the most between these two options: Option 1: A 9-5 job where you have to align your skills and results to achieve companies objectives, or.

Is data science dying out? ›

Data science will be around for quite some time. Data has become an indispensable part of the 21st Century with our society witnessing rapid digitalization in the last couple of years. Most companies worked to solve very similar business problems with data science.

Is AI going to replace data science? ›

Instead of posing a threat to data science jobs, A.I. will likely become knowledgeable assistants to Data Scientists, allowing them to run more complex data simulations than ever before. Analytical skills will soon be required in many more traditional roles.

Will data scientists still be in demand in 2022? ›

Data Science Career is the hottest and most demanded topic in the market among the youth in 2022. Data science includes advanced analytics techniques and scientific principles to extract valuable information from data for business decision-making, strategic planning, and other uses.

What is trending in data science? ›

Cloud and Data-as-a-Service

This reduces the need for companies to build their own expensive, proprietary data collection and storage systems for many types of applications. As well as raw data, DaaS companies offer analytics tools as-a-service.

Can I become a data scientist in 3 months? ›

In conclusion, I would say that it is hard to become a Data Scientist, especially in three months. This is because: Some Bootcamp is not qualified enough to teach you the necessary data science skills. Not every student are talented enough to catch up with the learning material in a short time.

Do you need high IQ to be data scientist? ›

It turns out as for most engineering field, IQ of 130 is minimum. As for data science, it turns out you need to have an IQ of 150 (3 std up above the average population).

Can I become data scientist in 4 months? ›

Altogether, the amount of learning that is required to become a data scientist cannot be done in a mere time period of six months.

Can data scientists become rich? ›

You could definitely earn enough to live a comfortable life if you decide to pursue a place in the industry. While the numbers differ from one source to another (Indeed reports it to be $120,099 per year, while Glassdoor states that it is $113,736), most data scientists earn above $100,000 yearly in the United States.

Is 1 year enough for data science? ›

People from various backgrounds especially with zero coding experiences have proven to become good data scientists in just one year by learning to code smartly.

Is 35 too old for data science? ›

It's never too late to start your data science journey. Although mid-career pivots can be daunting, it's possible to become a data scientist at any age.

Is 55 too old to become a data analyst? ›

You can become a data scientist at any age if you're willing to put in the work.

Who earns more MBA or data scientist? ›

The recent placement data from Symbiosis Pune reflects that a postgraduate program in Data Science when compared to a general MBA degree has better placement opportunities in terms of average salary and highest package offered.

Who gets paid more data scientist or data analyst? ›

As per Glassdoor, the average salary of a data analyst in India is 6 Lac rupees per annum. In India, the average salary of a Data Scientist is 9 Lac rupees per annum.

Which company hires most data scientist? ›

Data science jobs are known for their high starting salaries, high job satisfaction, and a high level of demand.
...
What companies are hiring data scientists?
  1. Accenture. 63,206 data employees. ...
  2. Tata Consultancy Services.
  3. IBM. 35,986 data employees. ...
  4. Citigroup. ...
  5. Deloitte. ...
  6. Infosys. ...
  7. JPMorgan Chase. ...
  8. EY.
16 Sept 2022

How much do Netflix data scientists make? ›

The average Netflix Data Scientist earns an estimated $164,977 annually, which includes an estimated base salary of $137,128 with a $27,849 bonus. Netflix's Data Scientist compensation is $35,768 more than the US average for a Data Scientist. Data Scientist salaries at Netflix can range from $70,000 - $270,000.

Is data scientist a stressful job? ›

Several data professionals have defined data analytics as a stressful career. So, if you are someone planning on taking up data analytics and science as a career, it is high time that you rethink and make an informed decision.

How much does a PhD in data science make? ›

Breaking down the Phd in data science salary for 2022, we see results in a significant salary bump: The average PhD in data science salary is $153000. At the IC-2 level, data science PhD salaries are nearly $17,000 higher than master's degree holders.

How old is the average data scientist? ›

Interestingly enough, the average age of senior data scientists is 40+ years old, which represents 41% of the population.

Is data scientist a hard career? ›

No, if one has learned the right set of skills, data science will not be a hard job for them. The field of data science is new and has not matured fully yet. So it might seem difficult when you start. But once you learn the nuts and bolts of it, it is not a hard job.

Can an average person become a data scientist? ›

If you have strong knowledge of algorithms, you can easily build data processing models. However, even if you don't have strong coding knowledge and a special degree in data science, you can still become a data scientist. With good learning capability, you can be a data scientist without a degree in it.

What is the hardest part of being a data scientist? ›

1) Finding the data

The first step of any data science project is unsurprisingly to find the data assets needed to start working. The surprising part is that the availability of the "right" data is still the most common challenge of data scientists, directly impacting their ability to build strong models.

Will data science still be in demand in 2030? ›

According to the United States Bureau of Labor Statistics (2021), the field of data science and computer information research is predicted to develop at a rate of 22 percent from 2020 to 2030, which is three times faster than the typical profession.

What is the highest position in data science? ›

Top 10 Highest Paying Data Science Jobs in India [A Complete...
  • Machine Learning Engineer.
  • Machine Learning Scientist.
  • Applications Architect.
  • Data Architect.
  • Enterprise Architect.
  • Infrastructure Architect. Top Data Science Skills to Learn in 2022.
  • Statistician.
  • Business Intelligence Analyst.
22 Sept 2022

Why do data scientists fail? ›

Lack Of Data:

For every project, the need for well-interpreted data is a must. Without the right quantity of quality data, it is nearly impossible to train any type of machine learning or deep learning model to achieve the most suitable results that a data scientist might look for.

Is life of a data scientist boring? ›

A typical day in the life of a data scientist is never boring or dull, instead, it is full of challenges and opportunities to learn new things and solve new business problems.

Is data science career is overhyped? ›

The problems above all stem from there being too much hype around data science. Students tend to rush into the field too quickly because they want to learn a skill that is highly in demand. Employers start mass hiring data scientists without completely understanding the role.

Is data science harder than AI? ›

Data Science vs Artificial Intelligence – Key Difference

The tools involved in Data Science are a lot more than the ones used in AI. This is because Data Science involves multiple steps for analyzing data and generating insights from it. Data Science is about finding hidden patterns in the data.

Which is better it or AI and data science? ›

The data science market is expected to reach USD 178 billion by 2025, while artificial intelligence (AI) is predicted to grow at a compound annual growth rate of 13.7% and is anticipated to grow USD 202.57 billion by 2026.

Is ML or AI better for data science? ›

There is much more to Data Science than just AI and ML. There is much more to AI and ML than just Data Science. There are ML techniques used in Data Science for performing particular tasks and solving specific problems. There are AI concepts — that are NOT ML techniques — employed in the field of Data Science.

How do I start a career in data science 2022? ›

How to Become a Data Scientist?
  1. Read up and understand the field well before diving in.
  2. Slowly developed and hone the right data science skills.
  3. Learn the fundamentals first.
  4. Practice key programming languages.
  5. Gather, understand, and visualize data using small case studies available on the internet.
26 Jul 2022

Is data scientist an it job? ›

A Data Scientist job is most definitely an IT-enabled job. Every IT professional is a domain expert responsible for handling a particular technical aspect of their organization.

How can I become a successful data scientist in 2022? ›

How to Become a Data Scientist in 2022: Four Essential Steps
  1. Understand what a data scientist does.
  2. Develop the traits and habits of a good data scientist.
  3. Learn the essential languages and software skills.
  4. Choose your educational pathway.

What are the key data trends for 2022? ›

7 Big Data Trends in 2022
  • Data Will Be Analyzed on the Cloud. ...
  • Predictive Analytics Will Be On the Rise. ...
  • Actionable Data for Improved Decision Making. ...
  • Clinical Analytics Will Continue Transforming Healthcare. ...
  • Artificial Intelligence and Machine Learning. ...
  • IoT (Internet of Things) Will Drive Streaming Analytics.

What is the next big thing in data? ›

Augmented Analytics

This is a data analytics concept that automates the analysis of large amounts of data using AI, machine learning, and Natural Language Processing technologies to offer real-time insights.

What are the 2022 digital trends? ›

Digital Trend #4: 2022 will be the year of the micro- and nano-influencer. Move over, celebrities and mega-influencers. Creators with smaller followings will be the strategic play in the influencer marketing world in 2022.

What is the minimum salary of data scientist per month? ›

What is the starting salary for a Data Scientist in India? Average starting Salary for Data Scientist in India is around ₹4.5 Lakhs per year (₹37.5k per month). 1 year of minimum experience is required to be a Data Scientist.

Can I be a self taught data analyst? ›

It's definitely possible to become a data scientist without any formal education or experience. The most important thing is that you have the drive to learn and are motivated to solve problems.

How many hours does it take to learn data science? ›

On average, to a person with no prior coding experience and/or mathematical background, it takes from 7 to 12 months of intensive studies to become an entry-level data scientist. It is important to keep in mind that learning only the theoretical basis of data science may not make you a real data scientist.

Is data science still in demand 2022? ›

Data Science Career is the hottest and most demanded topic in the market among the youth in 2022. Data science includes advanced analytics techniques and scientific principles to extract valuable information from data for business decision-making, strategic planning, and other uses.

Is data science still hot in 2022? ›

LinkedIn reported some of these jobs as being more popular than data scientists in its “Jobs on the Rise” reports for 2021 and 2022 for the U.S. Part of the proliferation is due to the fact that no single job incumbent can possess all the skills needed to successfully deploy a complex AI or analytics system.

Is data science a growing field 2022? ›

Job Outlook

Employment of data scientists is projected to grow 36 percent from 2021 to 2031, much faster than the average for all occupations. About 13,500 openings for data scientists are projected each year, on average, over the decade.

Is data scientist a good job in 2022? ›

So, if you are still wondering if data science is a good career choice in 2022 and beyond, the answer is a resounding YES.

Will data science exist in 2030? ›

Data science will continue to exist for a while. Over the past few years, the growing digitalization of our society has made data an essential component of the 21st Century. As a result, data scientists wouldn't have to come up with novel solutions to problems.

Will data scientists be replaced? ›

Some of them state that the role of a data scientist will be replaced by tools like AutoML, while others refer to data science as a “dying field” that will soon be surpassed by roles like data engineering and ML operations.

Are data scientists paid well? ›

One of the highest-paying careers in data science. Data Scientists earn an average of Rs. 116,100 a year, according to Glassdoor. As a result, Data Science is a very lucrative career choice.

Is data science a hard career? ›

Data science is a difficult field. There are many reasons for this, but the most important one is that it requires a broad set of skills and knowledge. The core elements of data science are math, statistics, and computer science.

Is data science need coding? ›

All jobs in Data Science require some degree of coding and experience with technical tools and technologies. To summarize: Data Engineer: Moderate amount of Python, more knowledge of SQL and optional but preferrable is knowledge on a Cloud Platform.

Is data science harder than computer science? ›

Data science is a significantly more in-demand and advanced field in comparison to computer science. Due to this, entering the field of data science requires a bit more effort than computer science.

Do data scientists make millions? ›

Indeed has an average salary of $120,000, while PayScale comes in a bit lower with $95,000. On the other end of the scale, levels. FYI has a data science salary median of $150,000 and an insane $238,000 median coming from those in the San Francisco Bay Area.

Do data scientists code? ›

In a word, yes. Data Scientists code. That is, most Data Scientists have to know how to code, even if it's not a daily task. As the oft-repeated saying goes, “A Data Scientist is someone who's better at statistics than any Software Engineer, and better at software engineering than any Statistician.”

What is the maximum a data scientist can earn? ›

Average starting Salary for Data Scientist in India is around ₹4.5 Lakhs per year (₹37.5k per month). 1 year of minimum experience is required to be a Data Scientist. What is the highest salary for a Data Scientist in India? Highest salary that a Data Scientist can earn is ₹26.0 Lakhs per year (₹2.2L per month).

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