Expert tips for hiring (and retaining) data scientists

With IT leaders increasingly needing data scientists to gain game-changing insights from a growing deluge of data, hiring and retaining those key data personnel is taking on greater importance.

Without enough trained, high-level data scientists to fill all the job openings out there, CIOs are working with HR and hiring specialists to find ways to attract applicants. And once they hire them, the trick is then to keep these highly sought-after employees from leaving for another job — especially at a competitor.

“Companies are struggling to hire true data scientists,” says Brandon Purcell, vice president and principal analyst at Forrester, a Cambridge, Mass.-based industry analyst firm. “It’s very, very challenging, especially if [the companies aren’t] the biggest brands and the biggest names. Data scientists have the alchemy to turn data into insights. … There’s a lot of thought going into how to hire and retain them.”

And that’s true in every industry, from healthcare to agriculture, to retail, manufacturing, finance, and beyond.

This uniquely skilled, relatively new breed of data experts gathers and analyzes data — both structured and unstructured — to solve real business problems, using statistics, machine learning, algorithms, and natural language processing. As big data wranglers, they can improve customer experience, drive new products, and find hidden patterns that will affect critical business decisions.

But there simply aren’t enough trained — not to mention experienced — data scientists for all the companies looking to harness them. To compound that problem, the fight to attract and hire these IT professionals is overwhelmingly led by tech and internet giants, such as Amazon, Google, and Facebook, which can offer an impressive brand name, along with a wide variety of project options, hefty salary packages, and stock options.

According to a 2021 Gartner research report, hiring senior data scientists is “very difficult,” and even finding junior-level data science talent is challenging. Similar findings came out of a 2021 Forrester report which noted that 55% of companies surveyed were looking to hire data scientists. The report also pointed out that 62% needed data engineers and 37% wanted machine learning engineers — both are key data science support roles.

And these jobs pull in solid salary packages. Gartner reported that a data scientist in Washington, D.C., with eight or more years of experience can expect to earn $174,000 a year, or $110,000 with two years of experience or less. In San Francisco, those corresponding numbers are $192,000 and $118,000. 

Yes, offering competitive or better money is a key factor when attracting skilled data scientists in this market. But it often takes more than that to land data science talent — and it goes way beyond in-office table tennis, Friday pizza lunches, and free bags of seaweed chips, as these IT leaders and industry analysts attest.

Focus on purpose

With 72.4 million active customer accounts and 7 trillion data points, Bess Healy, senior vice president and CIO at Synchrony, is always looking to expand her data science team.

“We, like many other institutions, are seeing a very large growth in our amount of data. It’s the fuel that feeds our insights,” Healy says of the Stamford, Conn.-based consumer financial services company. “Our need will continue to grow over time. We have to attract and retain these skill sets. We know we’re in competition every day for them. Staying ahead of our competitors is a big focus for us. We don’t feel behind but we have a very healthy focus on not falling behind.”

To find and retain strong data scientists, Synchrony offers flexible hours, continuing education opportunities, and remote work options, such as working from home or a hybrid home/office schedule.

For Anupam Khare, senior vice president and CIO at Oshkosh, their value proposition for attracting needed data scientists and other data experts is offering them inspirational projects to work on. The Wisconsin-based industrial company designs and builds a wide swath of products, including specialty trucks, military vehicles, and airport fire apparatus.

“We can give them meaning to their work. We basically design and manufacture products that help our communities and that’s a draw,” Khare says. “We manufacture products to serve everyday heroes — firefighters, soldiers, environmental and refuse workers. That is a very powerful and inspirational mission. … You can see that you have done an analytics model that helps production, and that means our firefighters get things on time and [get] better products. This is something real and you can feel it.”

The CIO also noted that Oshkosh focuses on groundbreaking technology for leveraging data to optimize its business, winning a prestigious CIO 100 Award, which honors companies for using IT in innovative ways, four years in a row. They also won the 2021 MIT Sloan CIO Leadership Award. That kind of reputation for inventive and engaging work helps attract professionals who want to do creative work.

The data science team at OshKosh also is given a wide spectrum of problems to tackle, working on issues that affect everything from manufacturing to sales and the supply chain. That not only diversifies their daily work; it also expands the teams’ skill sets, Khare explains.

“Within the digital tech team, we have a very innovative and progressive culture that focuses on trying new things and learning. They get to use new tech and get their hands on cool technology,” Khare says. “This is the place where you can bring ideas to life.”

Let innovators innovate

Giving data scientists cutting-edge technology and interesting projects to work on is key to attracting and retaining them, says Chandana Gopal, research director for The Future of Intelligence at IDC, a Needham, Mass.-based industry analyst firm.

Hiring managers and IT leaders need to remember that data scientists are highly educated and trained professionals, often with PhDs in math or data science. They crave difficult problems that are critical to the business and have a possible wider benefit to science, their community, or society. And if that problem has never been solved before, even better.

“If they’re bored with what they are doing, they will not stay,” Gopal says. “You have to make sure they are a valuable part of your ecosystem, that they’re not doing data prep, and they are working on the big, interesting questions. Make sure you team them up with people on the business side so they’re tied in to big business needs. And give them a support team of people who understand data.”

Companies also shouldn’t make promises they can’t keep, or have no intention of keeping, because retaining data scientists is just as difficult as it is to hire them in the first place.

“Let them see projects through to fruition. And if you have software that can do low-level or repetitive tasks, make sure you train people to use it to relieve your top data people of these jobs,” Gopal says. “Make sure they are challenged. Make sure they are valued. Show them that executives are committed to using data.”

Hiring tips and strategies

IT leaders such as Synchrony’s Healy and Oshkosh’s Khare agree that signing on top-level data science talent. But they, along with IDC’s Gopal and other IT leaders and industry analysts, offer the following advice for hiring and retaining these highly sought-after IT pros:

Offer purpose. Data scientists have a lot of job options. If they’re bored with what they’re doing, they will not stay. Pique their curiosity and drive by giving them cutting-edge projects, or by giving them work that furthers a cause. In particular, data scientists should be made to feel essential by giving them projects that are mission-critical to the company.

Free them up for impact. While data scientists can often perform the full gamut of data science tasks, from cleansing data to gleaning insights from models in production, data scientist are most effective — and happiest — when supported by a team. Free data scientists up to focus on creative work by bringing in data engineers and machine learning engineers to handle engineering work and data prep. It’s also worthwhile to identify your best data literate employees and include them as subject matter experts on your data science team, so they can support the true data scientists in driving value tailored to business needs.

Connect them to the business. Ensure your data scientists, or data science teams, aren’t working on an island by themselves. Connect them with the business team so they are collaborating on the most important questions and continually have a measurable impact on the business.

Build a pipeline of tools — and talent. In addition to ensuring your data scientists are supported by data engineers, implement smart software to handle low-level and repetitive tasks, and consider partnering with universities and colleges to create a pipeline of trained interns and new grads that will beef up your data science support team.

Train for ongoing success. As with any IT field, advances in data science techniques and tools are continually emerging. Help your data scientists keep sharp by offering continuing education, and give current employees the training they need to take on data analytics roles that will aid your true data scientists.

Compensate well. Of course, even with all that, if you’re not paying market rate, you’re facing an uphill battle. Make sure your compensation is on par with, or exceeds, that at other companies your size, and your competitors. And be sure your offer package includes competitive perks, such as the option of remote work and flexible work hours.