Careers

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Data Mining at ThomasNet

ThomasNet is an online listing of industrial products and services often used by engineers and industrial professionals. Like any website, when people browse ThomasNet they leave behind a trail of data about their activities. ThomasNet users produce almost a gigabyte of data every day. To analyze this wealth of data, we use J, a unique programming language whose syntax is a mathematical notation. While J is a powerful tool to analyze ThomasNet data, it can also be used to explore and learn about mathematics (there are some excellent books for this). Data analysis, often called knowledge discovery or data mining, is a new and increasingly important field (see ACM SIGKDD and KD Nuggets). While many companies have massive amounts of data, they are just starting to understand how to utilize it to answer important questions. At ThomasNet, we want to know more about how users interact with our website, and how they interact with the company websites we link to. For example, if we want to determine if a company is losing customers because their website is difficult to use or doesn't have what users need, we can look at our data to see if users are statistically likely to look elsewhere after a brief visit to their site. Or, if we want to know how the entire industrial marketplace is changing, we can apply predictive mathematical models to our data, and then advise industrial companies and investment firms about what products and services are going to be most important to users in the future. By applying mathematical thinking to analyze data, data miners are able to give definitive answers to many of the problems their employers face.


For more information about mathematical careers, see this page from the Mathematical Association of America.

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