How to Become a Successul Data Scientist

This is a guest post by Michael Koploy. Interested in guest blogging for this site? Click here.

Seemingly overnight, data scientists have been pushed into the online spotlight. In the October 2012 edition of the Harvard Business Review, the position of “data scientist” was labeled as the sexiest job of the 21st century. Job posting search engine Indeed.com confirms the rise in popularity of this position, showing 15,000 percent growth over the last few years.

But what is a data scientist, and what does it take to become one? The role originated in companies such as LinkedIn, Google and Facebook, where analysts were tasked with managing databases with terabytes, petabytes, exabytes and sometimes zettabytes of data. These individuals are more than just data wizards, however. They’re what SiSense’s Bruno Aziza calls, “business analysts plus.” Business skills are almost as important as programming and statistical-analysis skills for data scientists, as they’re often the bridge between executives and the world of Data.

If you’re an aspiring data scientist, here are three secrets to career success.

Secret #1 – Focus on Academics Before and After School

Knowledge of an obscure algorithm or an often-overlooked statistical model may be the difference between an unsolved problem and a solution, so it’s valuable to obtain advanced mathematical degrees. Degrees such as computer science, physics, machine learning or applied mathematics will provide future data scientists with the knowledge necessary to be successful.

After exiting academia, however, it’s important to stay in-touch with academia, and take advantage of the research that is coming out of Universities and think tanks. Subscribing to academic journals such as the IEEE PAMI and the Journal of Machine Learning Research is one way to do this.

Secret #2 – Become a Data Scientist by Becoming a Businessperson

Data scientists are tasked with deriving actionable insights from an organization’s data. Because of this, an advanced understanding of business principles is just as valuable as advanced computer science knowledge. Project management skills, for example, will greatly benefit data scientists that are tasked with managing an elite team of developers. Likewise, excellent presentation and communication skills will benefit data scientists as they communicate their findings to executives within the organization.

For these reasons, it’s important to read as much about personal development and how businesses are using data as it is to read about academic research in computer science and statistics. A great book for starters is Thomas Davenport’s Competing on Analytics.

Secret #3 – Workout and Flex Your Data Muscles

Data scientists often use a multitude of tools, applications and programming languages to complete everyday tasks. From R and SAS to Hbase and Hadoop, adding tools to your toolbelt will help round-out your abilities and increase your value to organizations. There are a number of online resources, such as Big Data University, to learn more about a particular language or technology.

Likewise, it’s important to test out your skills in the wild. Participate in open-source contests or data science competitions on websites such as Kaggle. Not only are these chances to boost your resume, but also a great opportunity to collaborate and interact with others within the community.

About the author

Michael Koploy is an Analyst for Software Advice, a company that reviews and comparisons business intelligence solutions. For more on the topic of career advice for data scientists, check out Koploy’s article on the Software Advice blog: 3 Career Secrets for Aspiring Data Scientists.