"Big data" is a well-known term used to describe the vast and complex information that is collected and available today. Just as the Internet showed exponential growth and usage over the years, big data is experiencing a similar gain.
Why? Technology has increased the volume of data being created. Daily use of the Internet and mobile devices is a driving force for big data. Every digital transaction or social media conversation produces information. Twitter users alone send 500 million tweets per day. The surge in data has become increasingly important to business. More data may lead to insights that enable businesses – and people – to make smarter, more strategic decisions.
Having the data is one thing, but being able to turn it into usable information is a whole other challenge. As businesses began to realize the value of data, they also discovered the need to analyze it – quickly and accurately. This need led to a career path that the Harvard Business Review once described as "the sexiest job of the 21st century" – the data scientist.
Data scientists are in demand.
Being a data scientist isn't just sexy; it's lucrative for those fortunate enough to land a coveted position in the field. According to the Bureau of Labor Statistics, the 2012 median salary was around $102,000 per year1 and the field is expected to grow at a pace faster than the average.
But in demand doesn't mean easy to get. Seventy one percent of employers surveyed by CareerBuilder said that computer and mathematical occupations are the hardest to fill2. While there are many jobs available, there are too few qualified candidates to fill them.
Preparing yourself to become a data scientist.
If you have your sights set on becoming a data scientist, then the job outlook is good. There is plenty you can do to prepare yourself, which begins by understanding what a data scientist does and building the core skills you need to succeed in the profession.
What is a data scientist?
The role of a data scientist is still relatively new, which means you will find a wide range of opportunities related to big data. You could land in a data-focused company, like IBM or SAS, where data is the core business. You might also work for a company that is data-driven, meaning they care about data and use it to make decisions, but it isn't their main business focus. And, of course, there are a many other job variations in between.
To get a better sense of what a data scientist does and how you might fit into the career, it can be helpful to read specific job postings. Search for "data scientist," but also expand your search to jobs like "data analyst" or "IT project manager," since you may find a data-related job function under a different job title.
Reading real job posting will not only give you a better idea of what the day-to-day functions of a data scientist are, but can also help you understand the skills, experience and education you'll need. Wherever you end up, be prepared for a job where you'll "make discoveries while swimming in data," according to the Harvard Business Review3.
Every data science job is different, but you need some basic skills.
Even though there is a lot of variety in the data science field, you will need to come to the table with a core set of skills, including:
- Computer Science: Computer science is a broad field of study that includes learning in IT project management, programming languages (like Python), database management and more.
- Statistics: You must be able to provide a statistical analysis of data to help make decisions, so you should has a basic familiarity with statistical tests, distributions, probability, etc.
- Machine Learning: Machine learning is the science of getting computers to perform functions without being directly programmed.
- Multivariable Calculus and Linear Algebra: Knowledge in this area can help you develop new ways of optimizing data.
- Communication: At some point, you'll need to find a way to effectively convey meaning from your data, and that happens when you understand the basics of effective communication and human behavior.
Start building your data portfolio now.
A career as a data scientist doesn't just happen overnight. In addition to gaining the necessary skills to perform the job, you'll need to meet people in the field, as well as a proven track record that showcases your abilities.
As you're completing your degree program, practice applying what you're learning to build a research-based data portfolio, or one created using real-world data. Consider creating a blog that chronicles your insights and showcases your coding skills. You might also think about entering data competitions or applying for fellowships. And finally, don't forget to research what employers might be looking for when hiring a data scientist.