• Support & get perks [https://www.patreon.com/c/learnbayesstats]!

• Proudly sponsored by PyMC Labs! Get in touch at alex.andorra@pymc-labs.com

• Intro to Bayes [https://topmate.io/alex_andorra/503302] and Advanced Regression [https://topmate.io/alex_andorra/1011122] courses (first 2 lessons free)

Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work [https://bababrinkman.com/]!

Chapters:

11:37 The Hard Tech Era
21:08 The Shift in Tech Work Culture
28:49 AI's Impact on Job Security and Work Dynamics
34:33 Adapting to AI: Skills for the Future
45:56 Understanding AI Models and Their Limitations
47:25 The Importance of Diversity in AI Development
54:34 Positioning Technical Talent for Job Security
57:58 Building Resilience in Uncertain Times
01:06:33 Recognizing Diverse Ambitions in Career Progression
01:12:51 The Role of Managers in Employee Retention
01:26:55 Solving Complex Problems with AI and Innovation

Thank you to my Patrons [https://learnbayesstats.com/#patrons] for making this episode possible!

Links from the show:

 * Alana's latest book [https://www.alanakaren.com/books] (Use code BAYESIAN for 10% off + a free interview preparation download PDF)
 * Alana’s Substack [https://alanakaren.substack.com]
 * Alana on Linkedin [https://www.linkedin.com/in/alanakaren/]
 * Alana on Instagram [https://www.instagram.com/alanakaren/#]
 * The Obstacle Is the Way [https://www.amazon.com/Obstacle-Way-Timeless-Turning-Triumph/dp/1591846358/ref=sr_1_1] – The Timeless Art of Turning Trials into Triumph
 * Courage Is Calling [https://www.amazon.com/Courage-Is-Calling/dp/1788166280/ref=tmm_pap_swatch_0] – Fortune Favours the Brave

#149 The Future of Work in Tech, with Alana Karen

Are you a researcher or data scientist / analyst / ninja? Do you want to learn
Bayesian inference, stay up to date or simply want to understand what Bayesian
inference is? Then this podcast is for you! You'll hear from researchers and
practitioners of all fields about how they use Bayesian statistics, and how in
turn YOU can apply these methods in your modeling workflow. When I started
learning Bayesian methods, I really wished there were a podcast out there that
could introduce me to the methods, the projects and the people who make all that
possible. So I created "Learning Bayesian Statistics", where you'll get to hear
how Bayesian statistics are used to detect black matter in outer space, forecast
elections or understand how diseases spread and can ultimately be stopped. But
this show is not only about successes -- it's also about failures, because
that's how we learn best. So you'll often hear the guests talking about what
*didn't* work in their projects, why, and how they overcame these challenges.
Because, in the end, we're all lifelong learners! My name is Alex Andorra by the
way, and I live in Paris. By day, I'm a data scientist and modeler at the
https://www.pymc-labs.io/ (PyMC Labs) consultancy. By night, I don't (yet) fight
crime, but I'm an open-source enthusiast and core contributor to the python
packages https://docs.pymc.io/ (PyMC) and https://arviz-devs.github.io/arviz/
(ArviZ). I also love https://www.pollsposition.com/ (election forecasting) and,
most importantly, Nutella. But I don't like talking about it – I prefer eating
it. So, whether you want to learn Bayesian statistics or hear about the latest
libraries, books and applications, this podcast is for you -- just subscribe!
You can also support the show and https://www.patreon.com/learnbayesstats
(unlock exclusive Bayesian swag on Patreon)! This podcast uses the following
third-party services for analysis: Podcorn - https://podcorn.com/privacy