Montana Tech alumnus says value generated by data scientists create long-term career opportunities in ever-evolving technology landscape

When you ask Chris Dienes (Mathematical Sciences, ’08) about the evolution of his career, his job titles have morphed over the past decade nearly as quickly as the frontier of Big Data itself.

“At my first job, I was called a statistician,” Dienes said. “Then it became data scientist, and later it was AI/ML (Artificial Intelligence/Machine Learning) engineer. Now you’re seeing generative AI (artificial intelligence) scientist. Some places still call it data science, and some places still call it machine learning, but we're doing similar things, while maybe some roles are just adding more emphasis to the latest technology and the hottest buzzword.”

Dienes’ latest role is senior data science manager at Atlassian, a software company. It’s a remote role that allows him to work from his home in Colorado. Dienes previously was an applied science manager at Amazon, where he used his skills to help one of the world’s largest companies optimize their advertising business. Since he earned his Ph.D. in Statistics from the University of California-Davis in 2013, Dienes has had the opportunity to collaborate with a number of partners on meaningful projects in both consulting and staff roles.

“I've had the opportunity to work in academic research settings, support national healthcare surveys at the CDC, perform R&D at large manufacturers, and deliver online advertising at scale,” Dienes said. “In pretty much any field, you find a need for data driven solutions. I think that's what makes data science cool. You can tackle a lot of different problems in a lot of different spaces.”

One of Dienes’ most interesting projects was completed in collaboration with the Wall Street Journal.

“We built a natural language search tool called Talk 2020 and it was hosted on the Wall Street Journal website,” Dienes said. “Since it was public facing, I could show it to my mom, which made it one of the coolest things I ever built. Talk 2020 allowed users to search for any quote from the 2020 presidential candidates occurring in the past 20 years. So, you could go in and say, ‘What has Trump said about God?’ or ‘What has Biden said about hot dogs?’ You could ask it anything, and then you'd get the most relevant quotes to your query. That was super cool because, you know, millions of searches were performed by potential voters during the election.”

In another project, Dienes collaborated with the Centers for Disease Control and Prevention (CDC) researchers who were utilizing fitness tracker data for a health study. Researchers worried that the device could be collecting data in such a way that the participants, who were supposed to be anonymous, might be identified.

“I essentially had to invent experiments to see if I could figure out if this activity monitor could be used as a spy device,” Dienes said.

In the end, Dienes found the researchers did need to take more steps to better anonymize the data.

While some people have worried about the future job market because of the rise of artificial intelligence and machine learning, it’s not something that stresses Dienes.

“I think when a new technology emerges, including powerful technologies like generative AI, it tends to be the case that these technologies don't directly replace people. Rather, it’s the people who learn how to use these new technologies who will replace the people that don't learn to use the new tools,” Dienes said. “I think that is a good reason to be really comfortable using AI, even if you don't go directly into data science. Ultimately, whether you are in statistics or machine learning or generative AI, whatever we want to label it, it all involves using data to answer impactful questions for the business.”

The Bureau of Labor Statistics predicts the job market for data scientists will grow 36% over the next 10 years, much faster than average. The Bureau reports the median salary for data scientists in 2023 was $108,020 per year, or $51.93 per hour.

The demand for data scientists is related to the value they produce.

“Ultimately, once you get into industry or even scientific research, the questions you're answering are driving significant change; such as changes in our scientific understanding or changes to how a business will address cost reduction or drive future revenue growth,” he said. “So, the opportunity to have outsized impact in your career is certainly large. Most companies view this role as an investment for their future.”

For more information or to apply to Montana Technological University’s data science program, click here.