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Why It Is OK to not be OK as a Data Scientist. (Mark Freeman) - KNN Ep. 69 episode artwork

EPISODE · Oct 13, 2021 · 1H 21M

Why It Is OK to not be OK as a Data Scientist. (Mark Freeman) - KNN Ep. 69

from Ken's Nearest Neighbors · host Ken Jee

Mark Freeman is a community health advocate turned data scientist interested in the intersection of social impact, business and technology. His life’s mission is to improve the well-being of as many people as possible through data – especially among the marginalized. As the founder of On the Mark Data, Mark uses this platform to share impactful ideas via content creation, as well as push for innovation through consulting startups. In this episode we dive we dive deep into mental health in the data science domain, something we both believe needs to be talked about more. We also talk about how community, systems, and culture can help breed resilience and success on our data science journey. I hope you enjoy the episode, I know I had a blast speaking with Mark.

Episode metadata supplied by the publisher feed · Published Oct 13, 2021

What this episode covers

Mark Freeman is a community health advocate turned data scientist interested in the intersection of social impact, business and technology. His life’s mission is to improve the well-being of as many people as possible through data – especially among the marginalized. As the founder of On the Mark Data, Mark uses this platform to share impactful ideas via content creation, as well as push for innovation through consulting startups. In this episode we dive we dive deep into mental health in the...

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Why It Is OK to not be OK as a Data Scientist. (Mark Freeman) - KNN Ep. 69

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This episode is 1 hour and 21 minutes long.

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This episode was published on October 13, 2021.

What is this episode about?

Mark Freeman is a community health advocate turned data scientist interested in the intersection of social impact, business and technology. His life’s mission is to improve the well-being of as many people as possible through data – especially among...

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