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Episode 6: Bullshit Jobs in Data Science (and what to do about them)
Manage episode 324626929 series 3317544
Hugo speaks with Jacqueline Nolis, Chief Product Officer at Saturn Cloud (formerly Head of Data Science), about all types of failure modes in data science, ML, and AI, and they delve into bullshit jobs in data science (yes, that’s a technical term, as you’ll find out) –they discuss the elements that are bullshit, the elements that aren’t, and how to increase the ratio of the latter to the former.
They also talk about her journey in moving from mainly working in prescriptive analytics building reports in PDFs and power points to deploying machine learning products in production. They delve into her motion from doing data science to designing products for data scientists and how to think about choosing career paths. Jacqueline has been an individual contributor, a team lead, and a principal data scientist so has a lot of valuable experience here. They talk about her experience of transitioning gender while working in data science and they work hard to find a bright vision for the future of this industry!
Links
- Jacqueline on twitter
- Building a Career in Data Science by Jacqueline and Emily Robinson
- Saturn Cloud
- Why are we so surprised?, a post by Allen Downey on communicating and thinking through uncertainty
- Data Mishaps Night!
- The Trump administration’s “cubic model” of coronavirus deaths, explained by Matthew Yglesias
- Working Class Deep Learner by Mark Saroufim
37 에피소드
Manage episode 324626929 series 3317544
Hugo speaks with Jacqueline Nolis, Chief Product Officer at Saturn Cloud (formerly Head of Data Science), about all types of failure modes in data science, ML, and AI, and they delve into bullshit jobs in data science (yes, that’s a technical term, as you’ll find out) –they discuss the elements that are bullshit, the elements that aren’t, and how to increase the ratio of the latter to the former.
They also talk about her journey in moving from mainly working in prescriptive analytics building reports in PDFs and power points to deploying machine learning products in production. They delve into her motion from doing data science to designing products for data scientists and how to think about choosing career paths. Jacqueline has been an individual contributor, a team lead, and a principal data scientist so has a lot of valuable experience here. They talk about her experience of transitioning gender while working in data science and they work hard to find a bright vision for the future of this industry!
Links
- Jacqueline on twitter
- Building a Career in Data Science by Jacqueline and Emily Robinson
- Saturn Cloud
- Why are we so surprised?, a post by Allen Downey on communicating and thinking through uncertainty
- Data Mishaps Night!
- The Trump administration’s “cubic model” of coronavirus deaths, explained by Matthew Yglesias
- Working Class Deep Learner by Mark Saroufim
37 에피소드
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