Whether you’re a self-defined Data Scientist or in the market to hire one, chances are you have your own definition of what this job entails. But that’s through no fault of your own – it’s simply the reality of a newly emerging field. Before you proceed, you’ll want to be sure you clearly understand the areas of expertise and skills of a true Data Scientist.
The Convergence of Disciplines In Data Science
So what exactly is a Data Scientist, as defined by databahn? As you know, a Data Scientist is an individual that crosses both educational and professional boundaries, evolving into a person of many trades. In this hybrid position, a Data Scientist must excel in a number of disciplinesincluding (but not limited to) Advanced Analytics, Business Acumen, Communication & Collaboration, Creativity, Data Integration, Data Visualization, Software Development, and Systems Administration.
With the combination of these specific areas of education and skills, it’s no wonder Data Scientists are often compared to unicorns. Much like finding a unicorn – a creature that lives in fictional worlds - it’s not a simple task finding someone who is proficient in each and every one of these areas of study. In fact, according to Berkeley Science Review, “historically, no single practice described the simultaneous use of so many different skill sets and bases of knowledge” (ref: “Data Scientist”).
The “Tools” You’ll Need Handy As a Data Scientist
In addition to the numerous fields, these professionals need to be experienced with several toolsincluding programming languages, databases, Hadoop distributions, visualization applications, business intelligence (BI) programs, operating systems, and statistical packages. While there are many options, the O’Reilly Data Science Salary Survey outlines the most popular ones used by those in the industry last year. If you want to identify yourself as a Data Scientist and make yourself more marketable, these are the tools databahn highly recommends mastering:
This is a vital component of the overall job, considering the amount of tools you have under your belt will increase your salary range.
Last year, the median salary for data science employees with knowledge of 1 to 10 tools was $82,000. And those exceeding 20 tools were looking at a median salary of $143,000.
The easy way to get around this is to organize all of the tools into correlations – or those that are most used together. This will undoubtedly make them easier to learn, and will easily increase your numbers in the process.
Mastering the Fundamentals of Data Science
Is education preferable over experience? This question often arises when a person is seeking a Data Scientist position. Many professionals and educational advisors firmly believe that you don’t need a particular degree to be successful in the field. In fact, the main focus is having the subject area expertise and the skills outlined above.
Of course, you can always take classes in whatever areas you’re lacking to amp up your resume. There are plenty of boot camp programs ranging in price from $0 to as much as $16,000. But don’t let the cost of the programs steer you in the wrong direction. While it may seem like a lot of money upfront, find comfort in the fact that it’ll pay off in the long run. You’ll at least break even with your improved skill set, but will most likely make a profit. Here are some bootcamps to think about, arranged in order of price:
- Data Science Fellows: Free (New York/Silicon Valley)
- Data Science for Social Good: Free (Chicago)
- Insight Data Engineering: Free (New York/Silicon Valley)
- Microsoft Research Data Science Summer School: Free (New York)
- The Data Incubator : Free (New York/Washington D.C. & Online)
- Data Society: $299-$399 (Online)
- Bit Bootcamp: $1,500 (New York)
- Data Science Dojo: $3,000 (Seattle, WA/Silicon Valley, CA)
- General Assembly: $4,000 (Boston/New York/San Francisco/Washington)
- Metis: $14,000 (New York)
- NYC Data Science Academy: $16,000 (New York)
The majority of Data Scientists today don’t have Data Science degrees precisely because it is a new field. After all, there are only dozens of schools that offer this program right now. This factor explains why there is little agreement on the necessary educational background. It is possible that as this field grows and develops, education will also take a front seat alongside experience. But until that time, remember that experience is key.
Become a Part of the Data Science Community
If you want to stay in the loop, keep track of all the Data Science events held worldwide. You’ll have the opportunity to expand your network of modern tradesmen, such as yourself. We live in a world where connections are key, so you may as well take advantage of the opportunity to build new relationships! Here are some events right around the corner: