Loyalty cards. Debit cards. Social media algorithms that determine what your feed brings up. Data and its analysis has not only gotten bigger, but more valuable and vital to daily living. Data science jobs, of course, follow suit.

Data science jobs have grown exponentially in recent year and is projected to jump 36 percent through 2031, a rate much faster than average for all occupations, according to the Bureau of Labor Statistics.

This continued growth and demand requires people up for the not-so-easy task, explains David Hornthal, president of Crosly & Associates, a boutique executive recruiting firm specializing in the analytics and data science industry.

“We have much more complicated methodologies and more advanced technologies,” says Hornthal, who worked as a data scientist before getting into recruiting. “It’s evolved into every single industry from sports to higher education to non-profits to hotels and airlines. It’s everywhere.”

About 13,500 openings for data science jobs are projected each year. Here are specific fields to keep an eye on.

Conversational AI
The emergence of ChatGPT has garnered this niche much buzz. Because it’s a new technology, it requires a lot of data, skill and perhaps patience. “It’s an area where a lot of people don’t have the experience, so it’s going to be learn-as-you-go,” Hornthal says.

Next Best Action
This new area is heavily used in the sales force. For example, a pharmaceutical sales rep has a pre-mapped plan for the day that includes sales goals and doctor visits. But one wrinkle can easily make that now old plan sub-optimal, or “they can enter this new information into the sales management system and it tells them what to do next,” Horthal says.

Risk Management
The recent Silicon Valley Bank debacle is a recent reminder that this specialty is not going anywhere. Any institution in the business of granting money will always rely on those in data science jobs to minimize various risks.

Marketing Analytics
Businesses constantly seek ways to better market and target their products and services to new and existing customers. Constant gathering and analysis of data is crucial to do that.

Pricing
Determining optimal price points for products or services isn’t as cut and dry as it used to be. Add dynamic pricing on top of that and you’ve got an even more fluid model to deal with. “You can vary it in a matter of milliseconds based on what’s happening in the market,” Hornthal says.

Revenue Management
This deals with expiring products – think airfare, hotels and sports tickets that have an expiration date or demand that fluctuates on factors like weather or a great pitching matchup. “The concept of a ticket face price means nothing,” Hornthal says.

Supply Chain
Estimating what is expected to sell, ensuring there’s enough inventory to meet demand and figuring out how it all gets to the places they need to be is crucial for companies to maximize profits and minimize loss.

HCI/UX (Human Computer Interaction/User Experience)
Reactions to color, fonts and placement of chat boxes are examples of how data science is used to help companies create optimal user experiences. “It’s done with big social media. They change one factor and see how customers react then figure out which works best,” Hornthal says.

Autonomous Driving
Significant AI goes into this, especially with a huge push coming from corporations like Uber and Tesla. “This is an area that will continue to use data science resources because it’s the most game-changing technology we could see in our lifetime,” Hornthal says.

Georgann Yara is a journalist based in Phoenix. Find her on Twitter @georgannyara.

Photo by Christina Morillo.