This feature first appeared in the Spring 2015�issue of Certification Magazine. Click here to get your own print or digital copy.

If you recognize the reference in the headline of this article, then I have not only dated myself, but I've also given you valuable insight into my thought process. Yes, I'm a "Trekkie" (Star Trek fan for those of you not old enough or geeky enough to have beamed up to one of the many iterations of Trek). For me, part of my love of Star Trek (especially in its original 1960s glory) stemmed not only from my fascination with the wonderful, only-in-your-imagination gadgets (many of which are now part of our daily lives), but the totally creative and out-of-box thinking that was sometimes required to save the day. (Which always happened.)Outside of the fact that Trek was television, and TV trains us to believe in happily-ever-after endings, Star Trek was all about possibilities: plucking order out of chaos, sifting through seemingly random events to find (and implement) creative solutions. A true Trekkie knows that there is no such thing as a no-win scenario!‍

Star Trek not only gave many of us our first glimpses of technologies to come, but it blazed a trail in terms of the show's approach to problem solving. The characters provided us with a first glimpse into new ways to quickly swim through large amounts of constantly changing data (and circumstances) by combining rock solid technical skills (Mr. Spock, after all, was practically a walking computer) with often non-related disciplines coupled with a dash of creativity and a healthy dose of imagination. In many ways, the derring-doers of Star Trek functioned much like the data scientists of today.

If you're not familiar with the role of data scientist, just wait you will be soon. Though the field is still emerging, a data scientist already commands a very rewarding salary. According to Indeed.com, the average salary for a data scientist as of November 29, 2014 was $123,000 annually. By most standards, that's a fairly healthy compensation for services rendered. Also, that's the current compensation. Indeed.com's records indicate that the average data scientist salary in June of 2012 was approximately $100,000. To judge by the salary growth alone over the past two years, it appears that the role of data scientist is not just emerging it's hot and in demand!

‍What is a Data Scientist anyway?

‍A data scientist is a relatively rare and unique breed. Part technical guru, part businessman and part creative genius, a data scientist takes the role of data analyst one step further. Unlike a data analyst, who typically collects, examines and reports on data from a single primary source, a data scientist examines data from multiple (and often seemingly unrelated) sources to come up with new insights and trends that others don't see.

Employers don't just look to a data scientist for reports on what the data collected means � they expect the data scientist to provide recommendations on how to use the information, either to create solutions to existing or emerging problems, or to provide their business with a competitive advantage. Data scientists are also master communicators, able to impart their vision to others in a way that is easily and readily understood. The recommendation of a data scientist can literally change the business direction of an organization.

‍What skills are required?

‍A successful data scientist needs to possess a number of skills, including technical, business and soft skills. I conducted a search on Indeed.com (almost 1,500 data scientist job postings) and LinkedIn (nearly 1,000 job postings in the seven days prior to my search) and reviewed many of the postings to determine exactly what employers are looking for in a prospective data scientist. After reading numerous postings, several trends began to appear.

First, data scientists need to possess solid technical skills, including proficiency in one or more programming skills as well as tools that promote data manipulation and statistical analysis. Candidates are also expected to have a solid background in areas such as computer science, mathematics, econometrics, physics, analytics, modeling, or statistics (most job postings I reviewed were looking for candidates with at least a master's degree or comparable experience in one or more of these fields). Advanced degrees (masters or Ph.D.) in one of the computer sciences were frequently at the top of the list.

‍Say that again?

‍Those seeking to enter the field of data science also need to possess excellent communication skills. While this might sound intuitive, it may not be as easy as you might think. I remember once asking a question to one of my senior architects which I thought required only a simple yes or no answer. I was part of the legal team and trying to interpret a contract in light of how the software was being used by the development organization.

I received a three-page analysis from the architect that left me more confused than when I asked the question. The problem wasn't that the architect didn't answer my question � he did. The problem was that he answered it in such a way that I didn't understand what he was trying to communicate. In Project Management 101 (so to speak), they teach you that communication implies the sender's responsibility to ensure that the information is received and understood.

A data scientist works with complex data which may not be easily understood by others and, unfortunately, data scientists don't work in a vacuum and won't always be communicating with other techno-gods. It's important for a data scientist to be able to present the data results gleaned and recommendations formulated in a manner that is quickly and easily understood by the decision makers in their organization. If a data scientist can't communicate his or her vision in a comprehensible manner, then the information and/or recommendations are useless to a business.

‍Wanted: Creative thinking

One of the more interesting requirements employers look for in a data scientist is creativity. It's so important that creativity was actually listed as a requirement in numerous job postings. I particularly liked the following job requirement: "Creativity in developing actionable recommendations(.)"It makes sense to me that creativity is so highly valued. After all, a data scientist isn't merely spitting out data and creating reports � that person is correlating information from many different sources and looking for insights or trends others haven't spotted through traditional big data analytical methods. They're also responsible for making recommendations which may change the future direction of a business organization based on their findings.

Finding solutions that others failed to identify requires someone with a highly creative, inquisitive nature. A data scientist is one who not only thinks outside the box, but finds out why the box is square and how to make it circular, if necessary.

Successful data scientists need to be subject matter experts in their field and possess not only broad, but deep, in-depth industry knowledge of the business area they work in. Without in-depth knowledge and understanding of their chosen field of business, it would be difficult for even the most creative and technically savvy among us to identify trends, make inferences, and create the solutions required of a data scientist.

‍Do I need special training?

‍The role of data scientist is still relatively new and, based on research, it appears that there is no one particular degree or credential that seems to be the "must have" in terms of landing the job. That being said, candidates interested in the role of data scientist will be well-served to have at least a master's degree in one of the math or science fields mentioned above. Several universities are now beginning to offer advanced degrees in data science, which those who are serious about a career in data science should additionally explore.

In addition, numerous certifications are beginning to emerge in recognition of the power of the role of data scientist in the IT world. The two data science certifications which appear to be noteworthy are Cloudera's Cloudera Certified Professional: Data Scientist (CCP: DS) and EMC's EMC Data Science Associate (EMCDSA). Those interested in a data science career should take a closer look at these certs.

‍Beam me up!

‍Do you love all things analytics? Big data? Making sense of seas of seemingly random data, or looking for (and finding) patterns or trends that others don't readily or easily see? Are you able to present your ideas in a visual form easily understood and grasped by others? Do you possess the technical, business and people skills required to be on the cutting edge of big data analytics? If so, then the role of a data scientist just might be right for you.