I've been having a lot of complex career conversations with folks recently, and thought it might be helpful to share some of the common questions we talk about since so many of us are thinking about these things. First, what do you *need*? Figure out your $#, which is how much you need to earn to pay your obligations without performance-limiting anxiety. Does your life require a certain amount of work flexibility? Can you absolutely not move?

It's easy to build data practice ethics into your data science interviewing process. Add a few questions mixed in with your standard tech interview, and pay attention to the responses.

For example: 1) You're working on a model for consumer access to a financial service. Race is a significant feature in your model, but you can't use race. What do you do?

Wrong: I use zip code, because that correlates with race.

Right: I remove race as a factor and accept lower accuracy.

This piece on the bot economy is excellent for many reasons! The presentation of data, code, and images in the story is fantastic.

One aspect of this story that was under-emphasized is Twitter's hostility to victims of impersonation.

I was one in 2015. Here's what happened...

https://twitter.com/cocteau/status/957613471151030273

I had just given a keynote at @ghc, and my account was getting a lot of attention. All of a sudden accounts popped up using my photo, bio, and tweets, under usernames like @hmason0 and @hmasonab. I heard from at least 25 people who were confused, trying to find the real me.