Constant growth is one of the most exciting benefits of a career in technology. The pace of technological innovation is rapid. New opportunities for career growth seem to arrive every few months. Harnessing innovations to improve your skill set is an important path to staying competitive in the marketplace. Lately, one of the more consistent upward trends has been a focus on data and data analysis. Businesses are continuing to realize just how daunting it can be to pull useful information from massive data sets. If you are looking to enhance your career opportunities, then gaining skills in the burgeoning field of data can be a rewarding path forward.
Unfortunately, wage stagnation is becoming an increasingly relevant problem for many, although careers in IT tend to avoid the worst of it. Despite unemployment reaching a 16-year low, wage growth has not kept up. The post “5 Reasons Wages Have Stagnated” (J. Glassman, June 2017) from the JP Morgan Chase Commerical Banking Blog points out:
… despite steady above-trend employment growth, wages have remained relatively stagnant, rising at only a 2.5 percent to 3 percent annualized pace over the past year.
One way to avoid being stifled is to improve your skill set. Adding proficiency in less common skills makes you more valuable to your current, and future, employers. There is data to back the assertion that the more common a skill is, the less valuable it is. Paysa found a negative correlation between the percentage of positions requiring a particular skill and the salary’s average pay. In “Silicon Valley’s Most Valuable Skills” (Paysa, Oct 2016), the authors support the claim that “… that skills considered to be less common often resulted in a higher salary.”
Source: Silicon Valley’s Most Valuable Skills (Paysa, Oct 2016)
One particular example worth considering is R. R appears near the $140K mark, although in less than 2% of current job postings. The percentage may be small, but the size is misleading. Analysts use R for statistical analysis and data mining. R and its parent field of data analysis are growing and have a bright future. We already see an explosion in data-centric jobs:
In fact, the US Bureau of Labor Statistics reports that the job market for various data analyst disciplines is growing at 27% annually—far exceeding the national job growth average, which is a mere 11%. (G. Mathew, “Five Ways Data Analytics Will Shape Business, Sports And Politics In 2016”, Jan 2016)
The general understanding of data as a valuable commodity is well known, but its impact on business decisions continues to grow every day. The sheer amount of data is also increasing over time. A recent article in the Economist, “Data is giving rise to a new economy” (Economist, May 2017), quotes an IDC estimate that the amount of data copied and created every year will top 180 zettabytes (or 180 trillion GB) by 2025. Businesses will need data engineers and data scientists to sort through all their data to make meaningful connections. Without proper data analysis and tools like R, all that information will remain incomprehensible.
Data based positions already compare favorably to other software careers, despite the field being young. Based on the chart above, we would expect to see jobs in the data management field on the high end of compensation which a quick search on Paysa.com confirms. For example, a Software Engineer has an average total compensation of $171K while a Data Scientist has a total compensation package averaging at $165K.
Software Engineer Average Salary
Data Scientist Average Salary
Data Engineer Average Salary
Self-teaching is one standard approach to learning. On most technology topics there are books and articles you can use. Another option is to consider online sources. Continuing our example, Udacity.com has a self-guided course on R called Data Analysis with R by Facebook. The benefit of an online course is the structure it provides. Online courses can also allow access to others who share your interest or subject matter experts.
A third learning option is a more formal learning experience. Formal learning can be through a school’s adult annex course or an online program. The benefit of this approach is the ability to have validation of your competency. A certificate of completion gives an employer confidence that you learned the topics. In the world of data, Udacity offers a nanodegree (more information on nanodegrees are available here) on Data Foundationsand becoming a Data Analyst. Receiving a nanodegree tells employers that you have achieved a level of success.
Demonstrable success is an important part of enhancing your skill set. Improving your skills is personally beneficial, but translating that improvement into a higher salary is also rewarding. If you can use that knowledge to get ahead of a trend, such as the growing need for data analysis, then slumps in wage growth won’t stand in your way. The best way to ensure success is to use real-world job data, like Paysa.com, to guide you down that path of success.
Related: Online Courses and Bootcamps