Hi ,
While everyone's scrambling to learn the latest AI tools, most data scientists are missing one key truth - the fundamentals of good data science haven't changed:
- Asking the right questions of
stakeholders and your data;
- Planning for project uncertainty - because project never go as expected;
- Understanding statistics and data processing fundamentals;
- Knowing when results make sense.
All of these are just as relevant now, as they were before ChatGPT hit the
scene.
What has changed? The speed of execution.
Tasks that used to take days now take minutes with AI tools. But speed without process leads to fast failures, not fast results.
In the latest episode of Value Driven Data Science, I'm joined by Dr. Brian Godsey, author of Think Like a Data Scientist, to discuss why the scientific process behind data science remains more critical than ever, and how it has evolved to harness today's powerful AI capabilities.
This conversation reveals:
- Why the seemingly basic question "Where do I start?" continues to derail data scientists' effectiveness and how mastering the right process can transform your impact [01:15]
- The three stages of the data science process that remain essential for career success even as AI dramatically changes how quickly you can execute them [11:07]
- How the accessibility revolution of generative AI creates new
career opportunities for data scientists in organizations that previously couldn't leverage advanced analytics [18:34]
- The underrated troubleshooting skill that will make you invaluable as organizations increasingly rely on "black box" AI models for business-critical decisions [20:21]
Master the timeless principles first. Then use AI to amplify them.
Listen now on Apple Podcasts or Spotify, or click the link below:
Episode 66: How to Think Like a Data Scientist
(Even While AI Does All the Work)
Talk again soon,
Dr Genevieve Hayes.
