Reference no: EM131800671

Statistician: The Hot Job of the Future

With the dramatic proliferation of digital data over the last several years, professionals in the fields of statistics and data analysis are becoming hot commodities. At top companies like Google and IBM, new recruits holding a PhD in a statistics field can land jobs with starting salaries as high as $125,000.

In a world where almost anything can be monitored or measured, the applications created through advanced data analysis are opening up a wealth of opportunities. The key is the statisticians. All the raw data in the world, in and of itself, is not very useful until its significance can be determined. That's why companies are calling on the statisticians to turn these treasure troves of raw data into applicable and actionable information.

Google, for example, employs statisticians to continuously find new ways to improve its search algorithms. Statistical analysts have been upgrading Google's crawler software, which is used to update its search index. Analytical improvements are helping the software better identify Web sites that are more frequently updated over Web sites that have gone dormant. Because of the scale of Google's operations (running the same operations billions and trillions of times), even incremental improvements can have a dramatic effect.

IBM is looking to take advantage of opportunities in the field as well, with the introduction of its Business Analytics and Optimization Services Department, by providing data mining and analysis services to other fi rms. The unit originally comprised 200 of IBM's top mathematicians, statisticians, and researchers, but the company plans to expand through training and new hiring to tap the expertise of over 4,000 staff members.

As many statisticians point out, however, the use of statistics is not without its challenges. If not carefully analyzed, the massive amount of data available can overwhelm statistical models, and even strong statistical correlations in the data do not necessarily indicate a causal relationship.

Still, as the explosion of available data continues, the ability to identify mathematically abnormal relationships in the data creates a wealth of opportunities. Organizations need to be able to properly explain these abnormalities though, and that's why they need the best analysts and statisticians. These skill sets are quickly becoming the kind you can take to the bank!

Questions

1. Where have you recently seen the use of statistics and data analysis where you might not have expected it? How was it being used?

2. Top companies are finding that many talented analysts and statisticians actually have backgrounds in other disciplines such as economics, mathematics, and computer sciences. How do you think these disciplines relate to and inform the approach to data analysis?