patchperfect

breaking down data science + colored sneakers at the office


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It’s our very first guest episode, and I couldn’t be more excited to welcome Rachel Levy: a brilliant data scientist with a master’s in AI and one of my oldest friends.

We’ve known each other for 25 years, from school playgrounds to wedding speeches, and today she’s helping us break down one of the fastest-moving and most influential spaces in tech.

Rachel shares how a conversation with her CEO 10 years ago changed everything, inspiring a bold pivot into data science. She talks about how she merged her real estate knowledge with a growing passion for analytics and machine learning.

In this episode, she explains it all the same way she would for her parents:

  • ​the difference between data science, AI, and machine learning
  • ​supervised vs. unsupervised learning
  • ​what terms like Boolean, multiclass problems, clustering, and K-nearest neighbors actually mean
  • ​how companies like Netflix and Amazon use recommender algorithms powered by data science to personalize what you see and keep you engaged
  • ​the distinction between data scientists and data engineers
  • ​the importance of building relationships at work and leaning on subject matter experts for industry insights
  • ​the data science starter pack (hello, Python)
  • ​how the field is rapidly evolving into AI frameworks like natural language processing and agentic AI, and which industries are being transformed as a result

And of course, we close with our lifestyle segment and share our thoughts on colored sneakers at the office, our favourite Amazon jewelry finds for work, and the iconic Effortless Pant from Aritzia.

You’ll be in good hands.


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patchperfectBy Kirin Sennik