A statistical analyst uses advanced mathematical techniques to analyze a set of data and draw conclusions. At the most basic level, a statistical analyst takes collected data and plots it before calculating a regression curve to describe the data set. Regression models may be useful for making future predictions, determining price points, and assessing seasonal trends. The statistical analyst also calculates the mean, median, mode, and standard distribution of the data set; once these values are calculated, a distribution curve can be created to describe the behavior of the system in question. Common distribution schemes include Gaussian, Poisson, and skewed distributions.
A primary example of a statistical analyst at work is in quality control. For example, in a call center setting, the statistical analyst can monitor the work of the center over a period of time and calculate average values and standard deviations for metrics such as call length and calls taken per day. The mean value would give a manager an idea of how long the average call duration is or how many calls the average agent takes in a day. The standard deviation would allow the analyst to come up with a distribution and determine what acceptable ranges of values would be acceptable. Once the distribution is in hand, a manager can then set target metrics for call agents. This allows managers to identify agents who are excelling and those who would need more training.
Statistical analysts usually hold a bachelor's degree in mathematics, computer disciplines, or the hard sciences. Most of them work in standard office conditions and are required to travel very little.
Statistical Analyst Tasks
- Develop and maintain programs for the statistical library, including associated documentation.
- Interpret data analysis and produce results and reports for a variety of audiences.
- Define, track, and model key variables and metrics, and provide recommendations and strategic direction.
- Analyze data using a variety of tools, algorithms, and models, including developing models.
- Connect with, quality control, and create interfaces to databases with a variety of data.