Two Careers Every Smart College Student Should Know About
If you have been studying math, physics, chemistry, economics, engineering (electrical, mechanical, or chemical), or some other field, you probably have the data and math skills for a career in data science or operations research.
Both are in high demand, pay well, and are needed everywhere: industry, software companies, consulting firm, supply chains, finance, healthcare, government, and non-profits.
With these careers, you will use data and math to save lives, save money, and solve tough problems1.
First, let’s start with the better known career in data science. This field has been hot for the last 10 years and likely to continue.
With data science (also called analytics or AI), you can do a variety of different jobs.
You can do mining data and creating visualizations that help people better understand the situation.
You can use machine learning algorithms for many things like predicting demand, recommending products, understanding when customers may be unhappy, setting prices, improving safety, finding fraud, recognizing images, or reading text.
And, a career in data science can take you right to the cutting edge in areas like self-driving cars or trying to understand general intelligence.
To learn more, there are plenty of books and free on-line courses. For books, I like Prediction Machines and Competing in the Age of AI. A good classic article that helped jump start the movement is Competing on Analytics. For courses, Andrew Ng’s courses or YouTube videos is a good place to start, but you can easily find more once you start searching.
If you want to go deeper, almost every university has a masters in analytics program. I teach in Northwestern’s program, and we’ve hired great people from Georgia Tech and the University of Chicago. I’ve seen lots of students go through these programs with the undergraduate degrees I mentioned above.
The second career, Operations Research2 , is much less known.
This field is part of data science. But, many data scientists don’t (and should) know about it.
Operations Research (OR) is poised to be one of the fastest growing jobs in the next 10 years. It is also the path I took back in the 1990’s. Back then, data science didn’t exist and this was the way to use data and math to solve problems.
What is OR? In my mind, it is about building a math model of a system and then using or building algorithms that allow you to optimize (or improve or understand) the system. I find the optimization algorithms interesting. You set up the models with lots of alternatives and constraints. Then, the algorithms sort through it all to come up with good decisions or answers.
This approach to problem solving is critical to the airline industry, helps run supply chains, helps hospitals better schedule surgeries and get nurses as close to their desired shifts as possible, and helps with humanitarian relief and other non-profits, disaster relief, to name just a few.
Here are some additional links to help you discover more about OR
INFORMS, the professional society for OR has an annual prize that shows the range of things you can do with OR. The 2022 award features scheduling US Census workers, helping GM reach their goal of zero emissions, zero crashes, and zero congestion, and increasing the output of critical medicine at Merck Animal Health . The 2021 award included the delivering food more effectively at the UN, making good on JD.com’s same day delivery promise, and fighting cancer at Memorial Sloan Kettering using optimization to better direct radiation to the cancer cells and avoid healthy tissue.
The INFORMS website has a good FAQ for people interested in the field (and lots of other resources.
Here is a good interview (you can find this as a podcast too) with Professor Laura Albert of the University of Wisconsin. She talks about how she ended up in OR from being good at chemistry in high school, to why she likes OR, to her Punk Rock OR blog, and to some of her work in applying OR to aviation safety.
And, since supply chains are in the news, Larry Snyder of Lehigh explains how OR and Machine Learning can help supply chains. I wrote an educational book on one aspect of supply chain— determining where to locate facilities.
I could write much more on both topics. I hope this inspired you to look more into these areas.
I would love to hear from you, with either comments to help people who are new to the field or if you have questions about these careers.
This is quote from INFORMS, the professional society for Operations Research and Analytics (data science). I think it is a nice way to summarize the type of work that is done in this career.
It also goes by industrial engineering, management sciences, and sometimes it is called optimization.