So you’ve heard you’re supposed to network. That’s the key in getting a job or establishing a reputation in your broader field, right? And it’s true that the importance of having a good network is supported by a lot of social sciences research. But if the thought of networking makes you cringe, you’re not alone. Many people equate networking to sending out millions of unsolicited Linkedin requests with no message, handing out 20 business cards at a meetup once a week, or sending emails to prominent data scientists with the subject line “Can I pick your brain?

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In part one of this post, I covered how to start becoming involved in the data science community and meet people in general. But what if you read a really cool post by someone and want to follow up with them? This post offers some thoughts on how you can most effectively reach out to specific people. Two important caveats to start, both inspired by other posts on similar topics. First, to quote Trey Causey: “I am not without sin, and I’m also still figuring all this out.

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About two months ago I put a call out to Rstats twitter. I had a working, short script that took 3 minutes to run. While this may be fine if you only need to run it once, I needed to run it hundreds of time for simulations. My first attempt to do so ended about four hours after I started the code, with 400 simulations left to go, and I knew I needed to get some help.

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A few weeks ago, I wrote about my experience giving my first data science talk. If you’re interested, the full talk is available online, as well as the slides. In this post, I wanted to share some suggestions for managing business challenges that I didn’t have time to cover in my talk. Why Business Challenges? Why devote a whole post and half a talk to business challenges instead of, say, cutting edge deep learning papers or the shiny new language for handling Big DataTM?

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A few weeks ago, I gave my first ever data science talk. Jared Lander, organizer of the New York Statistical Open Programming meetup, had been asking me to speak, and after about six months at Etsy I thought I could share what I’d learned about A/B Testing and its challenges. If you’d like to watch it, you can view the recording here. The talk starts around 9:00 and ends at 41:30, with the rest being Q&A (I tried to repeat the questions, so you should be able to follow that as well).

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Emily Robinson

Date Scientist at DataCamp

Data Scientist

New York