Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…
Tools of the Trade
We talk a lot on this podcast about the results of data science and software engineering work. We even talk about the process of doing data science and software engineering work. But one thing we haven’t shed much light on, until this month, is: what specific tools help a Data Science team — or any developer or data scientist similarly engaged in building a scalable and intelligent system — ...
Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…
Tools of the Trade
We talk a lot on this podcast about the results of data science and software engineering work. We even talk about the process of doing data science and software engineering work. But one thing we haven’t shed much light on, until this month, is: what specific tools help a Data Science team — or any developer or data scientist similarly engaged in building a scalable and intelligent system — actually do their work? We asked several data scientists, machine learning engineers, software engineers, designers, and product managers the same question: what is your favorite tool that helps you do your job? You’ll hear all their answers in this episode, including:
- Why some well-known tools fully deserve the hype
- Specialized packages for specialized purposes
- How to slow down and really force yourself to think about the problem
- How to avoid analysis paralysis
“I like banging out unstyled web forms as much as the next back-end developer, but when you have the experience of spending
all day in a tool, those ‘tiny’ things like icon consistency
really pay off.”
— Zac Bentley, Lead Site Reliability Engineer II
Read the full show notes, meet this month's guests, and learn more about Klaviyo in our Medium writeup!
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