Tracking down answers to your questions about data scientists

Do you need a data scientist? Want to be one or improve the skills you already have? Check out our Insights series.

Data scientists have been in the headlines ("Sexiest Job of the 21st Century") and compared to unicorns because of their rarity or suppositional nonexistence. So it's no surprise that they're highly courted and well-paid by many organizations around the world. When we launched this series in early 2015, we checked the Kaggle job board to see who was hiring data scientists.

• L’Oréal wanted to anticipate consumers’ needs.
• The Philadelphia 76ers needed to forecast plays, players, teams and seasons.
• The Weather Channel was looking to optimize online ad placement.
• For publisher Simon & Schuster, it was optimizing e-book prices.
• A residential cleaning service in San Francisco wanted to find which scents work best for homes.
• An internet radio start-up had tons of data and ideas but couldn't provide relevant playlists.

Several themes seemed common: the ability to draw insights from big data (Hadoop was often mentioned), familiarity with a range of programming languages and good communication skills. We begin to wonder:

• How do organizations know if they need or are ready for a data scientist? What can they help you do?
• Who are real-life data scientists? What do they do? Did they always yearn to be one and how did they get there?
• And finally, if you want to become a data scientist, what should you do?

Ready for a data scientist? Get advice from the experts.

For an introduction to this topic, we turned to Dr. Michael Rappa, founder of the Institute of Advanced Analytics at North Carolina State University. This was the first university in the US to offer a Master of Science in Analytics, and it has evolved to offer specific training for students interested in becoming data scientists. (There are now there are more than 60 other similar programs in the US, as well as others around the world.) Rappa gave us his take on the increasing number of data scientists’ jobs – he sees it as a trend that will continue. He also shares his opinion on what makes data scientists different from other types of analysts, statisticians and data miners. He provides advice for those looking to hire data scientists, and he has lots of ideas if you are seeking a successful career path in that field.

Tips for executing a successful data science strategy from TDWI.

Hiring a data scientist? We have the interview questions you need.

Real-life data scientists – yes they do exist!

After that, we wanted to talk to some data scientists ourselves. We asked around to see if anyone would agree to interviews about their jobs and training. And we can say – without doubt – data scientists do exist because we interviewed almost a dozen from around the world. We’ll be posting new Q&As frequently. We asked the same questions. See if you think there are familiar threads running through those conversations.

The thrill of problem-solving. The lure of large paychecks. How to become a data scientist.

By now, you may be thinking, “Wow, that sounds pretty cool. I wonder if I’ve got what it takes to be a data scientist. How would I get started?” In this section, we’ll add articles with advice for those who want to rule the world of big data. As mentioned above, many colleges and universities now offer degrees in data science as well as advanced training in analytical methods ranging from statistics, machine learning and data mining to predictive modeling and wrangling huge amounts of data. There are online options as well.

Learn more about SAS On Demand for Academics

And then the data scientist said...

Now that we've had this series up and running, we're hearing from data scientists on topics that interest them. We'll publish those stories here.

Taking a team approach to data science by Jennifer Nenadic

Check back often!

Once we got started, the stories poured forth. It’s definitely a hot topic and there’s a lot of information out there. We hope you’ll check back often to learn more about the no longer mysterious, but infinitely interesting, data scientist.