Double Your Data Salary in 11 Months, with Jess Ramos

Today's episode features the charismatic and intelligent Jess Ramos. A data analyst, Jess has grown a huge social-media following via her fun content on SQL, data science, tech advances and career growth.

More on Jess:

• Founder of Big Data Energy Analytics⚡️, a company that supports her in-demand courses on SQL and data analytics.

• Senior Data Analyst at Crunchbase.

• Previously worked as a Senior Risk Analyst and as a Data Analytics Manager.

• Her popular social-media content (on SQL, data analytics, data science, tech advancements and maximizing professional growth) has led her to amassing over 300k followers across LinkedIn, Instagram and TikTok.

• She holds a Bachelor's in Math and she also holds a Master's in Business Analytics from The University of Georgia.

Today’s episode will appeal especially to folks who are looking to grow their career or grow into a career in data analytics or data science.

In today’s episode, Jess details:

• How she more than doubled her data analyst salary in less than a year.

• The questionable value of data science bootcamps.

• Her controversial take on "girl math" that made a splash in international mainstream news.

• The unexpected viral post that launched her into social-media fame.

• Essential advice for anyone starting their data career journey

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Consciousness and Machines, with Jennifer K. Hill

Something different for you: In today's episode, Bella Shing interviews both Jennifer Hill and me on a broad range of questions related to A.I., intelligence, neuroscience and (*gasp*) consciousness!

Looking forward to hearing what you think of this episode format, which is unlike anything we've ever done before. If you like it, I'll do it again :)

Jennifer Hill is:

• Serial entrepreneur currently building OptiMatch, where she serves as CEO.

• Exceptional speaker (to audiences as large as 100,000!), including regular collaborations with the renowned Deepak Chopra.

• Host of the "Regarding Consciousness" podcast.

Bella Shing is a film producer (including working with Tarantino on "Kill Bill"!) and entrepreneur who co-founded Coherence Education. She leads the Lisbon chapter of Light DAO, the organization that hosted this recording in Portugal last week.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Career Success in the AI Era, with Deepali Vyas

Rapid A.I. advances can be intimidating: How can you approach your career so you flourish in the coming A.I. era? Find out from Deepali Vyas — a world-leading A.I.-exec headhunter — in today's episode.

Deepali is:

• Senior Partner and Global Head of the Data, A.I. and Financial Technology Practice of Korn Ferry, one of the world’s largest executive-search firms.

• Founder of ProFolios.ai, a video-centric, A.I.-enhanced professional-branding platform.

• Founder of Fearless+, a platform that empowers tens of thousands of young people for career success.

• Holds a Bachelor’s in Financial Mathematics and a Master’s in International Finance from the London School of Economics.

Today’s episode should be interesting to everyone. In it, Deepali details:

• How A.I. has driven a 10x increase in applications per position and how you can compete in this high-volume climate.

• Why technical skills are becoming "table stakes" and what will differentiate the best candidates in the A.I. era.

• An insider's view on the talent flows between Wall Street and Silicon Valley, and how you can capitalize on these flows in your career.

• The "green flags" to look for in potential bosses and employers.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

How to Become Happier, with Dr. Nat Ware

On most metrics, it's never been a better time to be alive. And yet, many of us are unhappy. In today's episode, Dr. Nat Ware explains why we're unhappy... and, mercifully, what we can do about it!

Nat:

• Is a renowned keynote speaker; he has one TEDx talk alone that has over 2 million views on YouTube (it forms the basis of the content in today’s episode).

• Is the social-impact entrepreneur behind 180 Degrees Consulting (the world's largest consultancy for non-profits) as well as Forté (a startup that facilitates cost-free reskilling of workforces).

• Holds both a doctorate in economics and an MBA from the University of Oxford.

Today’s episode should be fascinating to anyone. In it, Nat details:

• Why, despite life on this planet being better than ever before, humans are so unhappy.

• Concrete guidance on what you can do to become happier.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

AI Systems as Productivity Engines, with You.com’s Bryan McCann

Today, wildly intelligent Bryan McCann describes the Agentic A.I. behind his skyrocketing startup You.com and how it will lead to scientific discoveries human scientists couldn't dream of making. Don't miss this episode!

Bryan:

• Co-Founder and CTO of You.com, a prominent Bay Area A.I. startup that has raised $99m in venture capital (including a $50m Series B in September that valued the firm at nearly a billion dollars).

• Was previously Lead Research Scientist at Salesforce and an assistant on courses at Stanford such as Andrew Ng’s wildly popular machine learning course.

• Holds a Master’s in Computer Science, a Bachelor’s in Computer Science and a Bachelor’s in Philosophy, all from Stanford University.

Today’s episode should be fascinating to anyone interested in AI. In it, extremely well-spoken Bryan details:

• The philosophical underpinnings of the breakthroughs that led to the leading A.I. models we have today as well as the ones that will emerge in the coming years.

• How a coding mistake he made serendipitously revealed fundamental insights about meaning and language model alignment.

• Why he believes humanity is entering an existential crisis due to A.I., but nevertheless remains optimistic about the future.

• The fascinating connection between language models and biological proteins.

• Why A.I. systems might soon be able to make scientific discoveries humans could never dream of making.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in October 2024

It's unreal to be able to speak to folks like the guests I hosted on the SuperDataScience Podcast last month. ICYMI, today's episode highlights the most riveting moments from October.

The specific conversation highlights included in today's episode are:

1. UC San Diego neuroscience professor Dr. Bradley Voytek on how data science facilitates breakthroughs in our understanding of the brain.

2. Eloquent Natalie Monbiot on how lifelike, digital versions of ourselves can scale up our public-facing work.

3. Lightning AI CTO Dr. Luca Antiga on where he sees generative A.I. being most useful in our professional lives.

4. Gable CEO Chad Sanderson on how, when we work with data, we always need to think about how downstream users might come to interpret our data... which is why he finds data contracts so important that he's writing an O'Reilly book about it.

5. Polars CEO Ritchie Vink on the incredible specs (e.g., efficiency speedups) of his open-source DataFrame-operations library for Python.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

The 10 Reasons AI Projects Fail, with Dr. Martin Goodson

Most A.I. projects fail. In today's episode, the brilliant (and hilarious) Dr. Martin Goodson details the top 10 reasons why A.I. projects fail and how to avoid these common pitfalls.

Martin:

• Is CEO and Chief Scientist at Evolution AI, a firm that uses generative A.I. to extract information from millions of documents a day for their clients.

• Is Founder and Organizer of the London ML Meetup, which (with >15,000 members) is the largest community of AI/ML experts in Europe.

• Previously led data science at startups that apply ML to billions of data points daily.

• Was a statistical geneticist at the University of Oxford (where we shared a small office together)!

Today’s episode will be of interest to anyone even vaguely interested in data science, ML or AI. In today’s episode, Martin details:

• The 10 reasons why data science projects fail and how to avoid these common pitfalls.

• His insights on building A.I. startups that serve large enterprises.

• The importance of open-source A.I. development.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

PyTorch Lightning, Lit-Serve and Lightning Studios, with Dr. Luca Antiga

Lightning AI makes tons of tools that speed A.I. model dev and deployment, including the wildly popular open-source library PyTorch Lightning. Today, hear from hands-on CTO Dr. Luca Antiga how all the magic happens ⚡️

More on Luca:

• CTO of Lightning AI, which (as one of world’s hottest startups developing A.I. tools) have raised over $80m in venture capital.

• Is also CTO of OROBIX, an A.I. services company that Luca co-founded 15 years ago.

• Holds a PhD in biomedical engineering from Politecnico di Milano… and did his postdoc at the Robarts Research Institute in London, Ontario (coincidentally around the same time I was doing brain-imaging research there).

Today’s episode will probably appeal most to hands-on practitioners like data scientists, software developers and ML engineers, but any tech-savvy professional could find it valuable.

In today’s episode, Luca details:

• How Lightning AI's suite of tools (in addition to PyTorch Lightning, this includes Lightning Studios, LitServe and the Thunder Compiler) is making A.I. development faster and easier.

• The rise of small language models and their potential to rival LLMs.

• His journey from biomedical imaging to deep learning pioneer.

• How software developer’s work will be transformed by A.I. in the coming years.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Neuroscience Fueled by ML, with Prof. Bradley Voytek

Today's guest is the extraordinarily intelligent and well-spoken UC San Diego theoretical neuroscience professor, Bradley Voytek. He reveals how AI/ML is accelerating our understanding of the brain.

More on Brad:

• Professor in UC San Diego's Department of Cognitive Science, Data Science Institute, and the Neurosciences Graduate Program.

• Joined Uber as their first data scientist, when it was a 10-person startup, helping build their data science strategy and team.

• Outreach work has appeared in Scientific American, NPR... and Comic-Con!

• Co-authored the amusing book "Do Zombies Dream of Undead Sheep?"

Today’s episode has some brief exchanges that will appeal most to hands-on practitioners, but should overall be fascinating to anyone.

In today’s episode, Brad details:

• How large-scale data science and machine learning are accelerating neuroscience research.

• Discoveries his lab has recently made that overturn nearly a century of neuroscience doctrine.

• Insights on structuring data science education to balance technical skills with creative, practical problem-solving.

• Lessons from using data science to optimize Uber's early ride-prediction algorithms.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Are “Citizen Data Scientists” A Myth? With Keith McCormick

In a recent episode, Nick Elprin and I laughed that "citizen data scientists" don't exist. Keith McCormick joins me today to eloquently rebut us and demonstrate the clear value of low-code/no-code tools.

Keith is:

• Data Science Principal at the enterprise A.I. consultancy Further.

• Creator of dozens LinkedIn Learning courses on machine learning and A.I. with, in aggregate, over a million students!

• Author of four statistics books.

Today’s short episode should be of interest to just about any listener. In it, Keith details:

• Common circumstances where low-code/no-code data science tools are the best option for you, even if you are a coding whiz.

• Whether citizen data scientists are myth or reality.

• How AutoML fits into the data science workflow - and why it won't replace data science teams.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Polars: Past, Present and Future, with Polars Creator Ritchie Vink

Because of it's stunningly fast speed, Polars is an extremely popular open-source library for DataFrame operations in Python. Kinda unreal to have Ritchie Vink, Polars' creator, as today's guest!

Ritchie:

• Is CEO and Co-Founder of Polars, Inc., a startup that has raised $4m in seed funding to support his Polars open-source project.

• Previously worked as an ML Engineer, Data Scientist and Data Engineer at companies like adidas and KLM Royal Dutch Airlines.

• Holds a Master’s in Structural Engineering and worked as a civil engineer prior to catching the data-science bug.

Today’s episode will appeal most to hands-on practitioners like data scientists and ML engineers. In it, Ritchie details:

• How Polars regularly achieves 5-20x (sometimes 100x!) speed improvements over Pandas for most DataFrame operations.

• The Eager and Lazy execution APIs Polars offers and when you should use one or the other.

• Ritchie's vision for scaling Polars to handle massive distributed datasets.

• How we can continue to make data-processing efficiency gains even as Moore's Law slows down.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in September 2024

Another month, another set of invaluable conversations on the SuperDataScience Podcast I host. ICYMI, today's episode highlights the most fascinating moments from September.

The specific conversation highlights included in today's episode are:

1. Posit PBC engineering manager Dr. Julia Silge explains why Positron, the next-generation IDE she's leading development of, is better-suited to data scientists than any existing IDE.

2. PyTorch expert Luka Anicin provides his top tips for training more accurate and compute-efficient ML models.

3. Exceptional open-source developer Marco Gorelli on why Polars is anywhere from 10 to 100x faster than Pandas, the incumbent Python library for working with DataFrames.

4. Microsoft's Marck Vaisman on what companies hiring data scientists should be looking for... as opposed to what the typically (and mistakenly!) look for today.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Data Contracts: The Key to Data Quality, with Chad Sanderson

Before talking to Chad Sanderson, I had never heard of Data Contracts. Now, I'm a proponent of how critical they are for data quality within any platform. Listen in and you may become a proponent too!

Chad is our guest in today's episode. He's:

• An extremely smooth communicator of technical information.

• CEO and Co-Founder of Gable, a platform for data teams that has raised $7m in seed funding.

• Chief Operator of the non-profit Data Quality Camp.

• Author of the forthcoming O'Reilly book “Data Contracts”.

• His informative social-media posts on Data Contracts have enabled him to amass over 80,000 followers on LinkedIn alone.

Today’s episode will appeal most to folks who work with data hands-on or who are involved in management roles that oversee data flows. Init, Chad details:

• What data contracts are.

• The critical concept of "shifting left" in data quality and governance.

• How data debt accumulates and leads to "spaghetti" data architectures.

• Why data quality is fundamentally a change-management problem.

Thanks to Emily Pastewka for suggesting Chad as a guest on the show!

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Virtual Humans and AI Clones, with Natalie Monbiot

Today, the clever and astoundingly well-spoken Natalie Monbiot provides a fascinating, mind-expanding episode on virtual humans, A.I. clones and the emerging virtual-human economy.

Natalie:

• Is Head of Strategy and a Founding Team member of Hour One, a leader in virtual-human video generation that raised $20m in a Series A led by Insight Partners.

• Through her own consultancy, EKLEKTIK, she advises virtual-human and A.I.-clone companies.

• Regularly speaks at the world's largest conferences, including Web Summit and SXSW.

• Holds a Master's in Languages and Literature from the University of Oxford.

Today's episode will of interest to everyone. In it, Natalie details:

• What virtual humans are.

• How virtual humans will buy us time and unleash a virtual-human economy.

• The ethical quandaries and challenges associated with creating virtual twins.

• What distinguishes virtual humans from deep fakes.

(P.S.: This is the first time we've ever shot an episode with three video cameras... if you watch the video version, let me know if you think it's worth the extra effort and investment!)

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

The Skills You Need to Be an Effective Data Scientist, with Marck Vaisman

Based on extensive research and analytical evaluations, in today's episode Marck Vaisman details all the skills that are essential for today's data professional.

Marck:

• Has been at Microsoft for seven years; for 5+ years, he’s been a Senior Cloud Solutions Architect, specializing in data, data science and AI/ML.

• For nearly a decade he’s also been an adjunct professor at both Georgetown University and The George Washington University, teaching graduate-level courses on math, stats, analytics and decision sciences.

• Co-Founded a non-profit in Washington, DC that runs both the Data Science DC and Statistical Programming DC Meetups.

• Holds a Bachelor's in Mechanical Engineering from Boston University and an MBA from Vanderbilt University.

Today’s episode will be of interest to anyone who is, manages, or aspires to be a data professional.

In today’s episode, Marck details:

• The skills, competencies and personas that data scientists and related professionals (such as analysts, data engineers, ML engineers and A.I. engineers) can have.

• The academic research on why “data scientist” is such a difficult job title to define.

• A comprehensive characterization of the essential skills that every data professional needs to be effective and the skills that allow you to specialize as a particular subtype of data scientist.

• The implications of all of this for both folks hunting for a data role and the companies that are looking to hire them.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.