Data Science: Data Culture and Career Tips at WiDS2017

February 9, 2017

On Friday, Feb. 2, it was my honor to speak at Stanford University’s Stanford Women in Data Science Conference 2017 to a live audience of 400 women in data science and a live-stream audience that spanned 25 countries on 6 continents hosting 75 WiDS events. What a movement! The event featured data science leaders from academia, industry, non-profits, and government talking about research, technology, and careers in the field. Attendees ranged in experience from current students to B.Sc.s and Ph.D.s. In all, 114 companies and 31 universities were represented. The energy and intelligence on display were truly inspiring.

At LinkedIn, one of our goals is to bring opportunity to every member of the global workforce. On a career-focused panel discussion aimed at helping and inspiring women to enter or stay in data science, I shared experiences, lessons learned, and suggestions for navigating career decisions in our field. A few high level points:

  • Right now, the demand for data scientists exceeds the supply, so if you’re interested in joining this field, it’s a great time for growth.
  • Data science is an evolving field. There are many flavors and specialities. This can also mean that things like terminologies and toolkits change frequently. A “data engineer” at one company may be called “data scientist” at another. Don’t worry—we’re all evolving together, so don’t think that you’re the only one who is confused sometimes!
  • Don’t doubt yourself because you don’t have a certain background or skill set. There is no one path to this profession, so you will forge your unique way. Data science is diverse!

If you are interested in more detail, I recommend you read my Forbes interview on how to launch a career in data science, or this one on how to excel in it, or watch the WiDS livestream recording here, starting at the 06:01:45 mark.

I also had an opportunity to speak to theCUBE about the data culture at LinkedIn, how we invest in tools to make our data scientists more productive, and how our data influences decisions at LinkedIn. You can watch the full interview here:

For anyone who is thinking of starting a career as a data scientist, I have one final piece of advice: ensure that you are joining an organization that values data and has a good data culture, or one where you can work on building a good data culture.

More on that last point and what I call #DataScienceHappiness in a future post. Stay tuned!

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