This is your first job, and you are nearly a year into it. You’re now coordinating a membership marketing campaign for a chain of hotels. You’re not unhappy about what you are doing, but after nearly a year, you’re looking for something different. You have a degree in information technology, and you want to pursue a career that’s more in line with your educational background.
Data science is all the rave right now. You’re also a sports fan, and you’re familiar with how teams in the NBA, like your favorite Houston Rockets, now rely heavily on big data and the resulting analysis. It will be ideal for you if you could find yourself working for one of the dominant teams in professional sports. Your goal is to pursue a career in data science. While working in professional sports is one option, what are the other opportunities in a data science career? How does one prepare do become a data scientist?
Overview of Data Analytics Profession
There is a reason for the rave. Companies have shown that decisions based on data analytics can be positively transformational. The Houston Rockets rose to the top of the NBA regular season rankings in 2018 with a .793 win-loss percentage, after languishing in the .500 range a decade earlier. Talent has something to do with it, but so is the use of data analytics.
This is the kind of impact people in data science can produce for organizations. Career-wise, you could live comfortably with the profession as the Bureau of Labor Statistics reports that the median annual salary is just below $118,500. With 31,700 jobs recorded in 2018, the ten-year growth outlook is expected to reach 16%.
Where to Start
You now have some understanding of what you might earn and how the profession creates an impact on organizations. Here are a few more things that you should know about pursuing this career:
- The role that fits right. One of the critical steps you need to take is to find out what role fits you best because there are varied positions in the field. Those that track the movements of basketball players gather data and are called machine learning experts. There are roles explicitly focused on visualization. Data scientists or data engineers are also typical positions that companies are looking to fill. Build your credentials and take courses if you need to fit in the specific role you are targeting.
- Skills. You must have some level of programming skills, preferably in R or Python. Experience in relational databases and SQL are critical skills to have as well. Strong initiatives, dedication, and a high level of organization are some of the practical skills you need to have. You must also be an excellent communicator, with the ability to inform effectively about the conclusions and solutions derived from analyzing data.
- Get out there and explore. Experts advise that you join a group of people who share the same interest in the profession. Motivation is crucial as you pursue this career, and interacting with the same group of people can provide you with motivational insights. Think of it as an AA group, only without the baggage of addiction. If there are events announced on online chatter, participate in the event.
You need to invest in learning to jump-start your career as a data scientist. There are online courses available. Further down the road as you pursue roles in leadership positions, an advanced program will help. But these three main points should set you in the right direction.