Predict scenarios to help a company plan for the future.
What does a Statistical Modeler do?
A Statistical Modeler’s job is to collect quantitative data culled from experiments, product testing, simulation, surveys, etc. — anything that can be measured and counted, such as sales, pricing, spending, employees, output, etc. — then analyze it using mathematical equations called “statistical models.” The Statistical Modeler’s goal is to develop forecasts and conclusions that will help a company make business decisions based on probability.
After all, business is a lot like gambling. Although it often feels like a matter of good luck and bad luck, the pros know the truth: Winning is all about knowing the numbers and playing the odds, which is why companies hire Statistical Modelers.
For example, when you’re a Statistical Modeler, a manufacturer that wants to know how rising gas prices will affect its business might pay you to model different scenarios to determine how a $0.05, $0.10, $0.50, $1, or $2 rise in gas prices could affect the cost of producing its products, and how that, in turn, could affect prices and, ultimately, sales and revenue. Then, it might ask you to determine the likelihood of each scenario so it can prepare itself for impending circumstances and make decisions that optimize outcomes.
Your typical day as a Statistical Modeler is spent designing, developing, and executing statistical analyses, and using software to create and solve mathematical equations. You also plot and graph data, and choose appropriate statistical models and statistical modeling techniques, such as regression and segmentation. In addition, you interpret data for your company’s decision-makers.
In the end, though, you’re basically a business Bookmaker, taking mathematical bets on your company’s future and doing your best to stack the deck in its favor.