10 min listen
How to pick projects for a professional data science team
How to pick projects for a professional data science team
ratings:
Length:
31 minutes
Released:
Mar 19, 2018
Format:
Podcast episode
Description
This week's episodes is for data scientists, sure, but also for data science managers and executives at companies with data science teams. These folks all think very differently about the same question: what should a data science team be working on? And how should that decision be made? That's the subject of a talk that I (Katie) gave at Strata Data in early March, about how my co-department head and I select projects for our team to work on.
We have several goals in data science project selection at Civis Analytics (where I work), which can be summarized under "balance the best attributes of bottom-up and top-down decision-making." We achieve this balance, or at least get pretty close, using a process we've come to call the Idea Factory (after a great book about Bell Labs). This talk is about that process, how it works in the real world of a data science company and how we see it working in the data science programs of other companies.
Relevant links: https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/63905
We have several goals in data science project selection at Civis Analytics (where I work), which can be summarized under "balance the best attributes of bottom-up and top-down decision-making." We achieve this balance, or at least get pretty close, using a process we've come to call the Idea Factory (after a great book about Bell Labs). This talk is about that process, how it works in the real world of a data science company and how we see it working in the data science programs of other companies.
Relevant links: https://conferences.oreilly.com/strata/strata-ca/public/schedule/detail/63905
Released:
Mar 19, 2018
Format:
Podcast episode
Titles in the series (100)
Hunting for the Higgs: Machine learning and particle physics go together… by Linear Digressions