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Join Ads Marketplace to earn through podcast sponsorships.
Manage your ads with dynamic ad insertion capability.
Monetize with Apple Podcasts Subscriptions via Podbean.
Earn rewards and recurring income from Fan Club membership.
Get the answers and support you need.
Resources and guides to launch, grow, and monetize podcast.
Stay updated with the latest podcasting tips and trends.
Check out our newest and recently released features!
Podcast interviews, best practices, and helpful tips.
The step-by-step guide to start your own podcast.
Create the best live podcast and engage your audience.
Tips on making the decision to monetize your podcast.
The best ways to get more eyes and ears on your podcast.
Everything you need to know about podcast advertising.
The ultimate guide to recording a podcast on your phone.
Steps to set up and use group recording in the Podbean app.
Harnhams McElla Pappas Weber, Sam Jones and Kyle Anzalone get together to discuss the key findings of the 2023 US Salary Guide. They discuss everything from the top reasons data professionals leave a role, to remote working, and of course the hot topic of AI as well as much more.
00:00-03:40 Intro.
03:40- 12:00 Job security in the data industry.
12:00- 19:45 Does company culture matter more than compensation for candidates leaving their current role?/What are the main reasons people leave?
19:45 – 20:33 Are you seeing hiring trends for hiring chief ML/AI management positions?
20:33-22:07 Who’s seeking jobs right now, are middle management positions or entry/senior level positions more sought out?
22:07- 24:28 Do you think hybrid/remote work models are here to stay long term?
24:28-27:06 With the rise of AI/ML are there fewer core analytics roles?
27:06-28:42 How has the current recession impacted the data industry?
28:42- 33:27 What’s driving movement and attracting talent in the marketplace?
33:27-35:57 Is equity not a prime factor?
35:57 41:30 AI
41:30- 45:15 Top 5 technologies used by data professionals.
45:15- 47:47 Do you think diversity of tools used in the data industry is a challenge for job seekers?
47:47-49:32 Within data and tech, are you seeing a trend of employees needing to do ‘everything’ (data architecture, data engineering etc.)?
49:32-53:10 What skills should be considered for a candidate ‘upskilling’ themselves?
53:10-54:32 How do you differentiate the requirement in learning Excel and PowerBI? Which one is more powerful?
54:32- 56:41 Wrapping up.
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