Data Science is an umbrella term that encompasses fields like data mining, machine learning, big data, data visualization, business analytics, bioinformatics, and statistics. Used in almost every industry big and small, data science comes in three main flavors:
- Inquiry – This form of data science is used widely by academia, governments, and research institutions to gain better understanding of both human and natural phenomena. One mission critical example can be found in the World Health Organization Collaborating Centers for Reference and Research on Influenza. Year round, the WHO coordinates with over 100 national influenza centers in over 100 countries to monitor the spread of influenza (Source: CDC).
- Analytics – This form of data science revolves around decision making, and is the most common form of data science found in the business world. On the customer facing side, data science is used to drive sales by determining, for example, where in a store to place a product, what keywords to target in a search, or what features to include in a product to target particular customers. Behind the scenes, data science is used to improve process quality, evaluate cost saving measures, and evaluate employee performance.
- Intelligent Machines – While analytics allows a user to make data driven decisions, intelligent machines take it a step a further, and make these decisions themselves. These tools play a huge role in automation, especially in the IT industry where intelligent machines are battling each other for ad space and user attention. A new up and coming intelligent machine is the self-driving car. Who knows where else in our lives we will soon find intelligent machines?
A career in data science will often entail taking part in two or all three forms of data science. To use weather forecasting as an example. First, researchers try to understand weather phenomena by refining theories and models with more and more data. While phenomena like rain are mostly understood, other phenomena like tornadoes are still at research stage (Source: PBS NOVA). Once a theoretical framework is established, they may next build a forecasting model to predict future phenomena, an intelligent machine. They may then be asked by governments to serve as analysts as officials try to balance the cost and risk associated with a mass evacuation against the risk and cost of partial evacuations or shelter in place orders.
The possibilities available for data scientists are endless.
“Data Scientist: The Sexiest Job Of The 21st Century”
– Harvard Business Review
Job Prospects
The field of data science is expected to grow 28% by 2020 according to IBM (Source: Forbes). Companies from different industries need data scientists and analysts to make sense of big data and to create a business strategy from that information.
| Job | Growth1 | 2016 Median Salary1 |
|---|---|---|
| Actuaries | 18% | $100,610 |
| Computer Systems Analysts | 21% | $87,220 |
| Economists | 6% | $101,050 |
| Financial Analysts | 18% | $81,760 |
| Market Research Analysts | 19% | $62,560 |
| Mathematicians | 21% | $105,810 |
| Operations Research Analysts | 30% | $79,200 |
| Statisticians | 34% | $80,500 |