Positioning is a common problem for data scientists
With the commodification of data scientists, the problem of positioning has become more common: My takeaways from Genevieve Hayes interviewing Jonathan Stark.
Data Business
Advice for aspiring data scientists and other FAQs
Frequently asked questions by visitors to this site, especially around entering the data science field.
Miscommunicating science: Simplistic models, nutritionism, and the art of storytelling
Nutritionism is a special case of misinterpretation and miscommunication of scientific results – something many data scientists encounter in their work.
You don’t need a data scientist (yet)
Hiring data scientists prematurely is wasteful and frustrating. Here are some questions to ask before you hire your first data scientist.
Data’s hierarchy of needs
Discussing the hierarchy of needs proposed by Jay Kreps. Key takeaway: Data-driven algorithms & insights can only be as good as the underlying data.