Data scientists are a hot commodity, sitting at no. 1 on Glassdoor's Best Jobs in America list for 2016, 2017, and 2018. Demand for these professionals has also boomed: Job postings for data scientists on Indeed.com rose 75% from January 2015 to January 2018.
Data science is a multifaceted profession involving computer programming, data visualization, artificial intelligence (AI), mathematics, database administration, and business intelligence—to name a few skillsets. The main value for data scientists in business lies in their ability to interpret data. "Nearly every company now has the ability to collect data, and the amount of data is growing larger and larger," explained TechRepublic's Alison DeNisco Rayome. "This has led to a higher demand for employees with specific skills who can effectively organize and analyze this data to glean business insights."
SEE: Job description: Data scientist (Tech Pro Research)
Unfortunately, the demand for data scientists is surpassing the available supply. And many of the emerging workers don't have the skillset necessary for positions, according to PwC. And data scientists who do have the necessary skills can be difficult to retain.
Retaining data science talent is difficult under normal circumstances, but in the event of a merger or acquisition, the challenge is even greater. "Acquisitions are a quick way to obtain AI expertise, which, at this point, is very scarce," said Jeff Loucks, executive director of Deloitte's Technology, Media, and Telecommunications Center. "When we think about what data scientists want to avoid, it's things that tend to come along with acquisitions."
Mergers completely alter the dynamic of a business, often diminishing the original goals and strategies of the acquired company. Data scientists are extremely affected by their work environment, according to a recent Deloitte study co-authored by Loucks, and business mergers can amplify problems that already exist, or create new ones, making them more likely to seek work elsewhere.
Here are five ways to retain your data scientists during and after a merger.
1. Nix office politics
Office politics are the biggest contributing factor in retaining data scientists, according to Loucks. The concept of "office politics" refers to employees' concerns with job security and promotions—worries that can be exacerbated during an acquisition.
"Many AI workers are at 'millennial-friendly' start-ups, and fully 60 percent of them say they do not have to deal with office politics in their current jobs," the study stated. "Of course, integrating an acquisition can create just the sort of uncertainty and 'office politics' that send data scientists heading for the exits. 'Where are we going? Who's going to be our boss? How come he's a VP now?'"
Data scientists don't put up with these hostile work environments and aren't afraid to take their expertise elsewhere, Loucks said. If you want to keep your data scientists, or keep the data scientists you are acquiring, then you must establish an office environment as free of negative politics as possible.
2. Define the role
Mergers or acquisitions typically bring at least two different companies together, which can cause confusion for the employees being acquired. The values their company had will likely be subsumed by the values of the larger company, leaving some employees in a state of motivation limbo.
"Often, data scientists are working for companies that are smaller. Maybe they're startups. Maybe they have an inspiring founder, and that they don't doubt their mission. They know what they're there to accomplish. That can become cloudier when they're acquired," explained Loucks.
See: Severance policy (Tech Pro Research)
It's vital that the companies acquiring these data scientists are clear on the company's vision, what data and AI they want to work with, and how data scientists are going to play a role in the execution, said Loucks. In order for data scientists to feel useful, they have to know their purpose at the company.
3. Communicate across business and tech
Along with communicating the role of data scientists, business leaders also need to communicate the role of data in their business. Data scientists can better study data if they know why the data is being gathered. However, Loucks refers to the relationship between data scientists and business executives as a "gulf in communication."
"Executives and data scientists don't speak each other's language," said Loucks. "Sometimes this is because executives expect data scientists to understand details of a business and to uncover insights based upon this assumed knowledge. And sometimes data scientists know the data science, as it were, better than they know the business."
This miscommunication can be debilitating to data scientists, leaving them with feelings of inadequacy and dissatisfaction, said Loucks. If end goals are communicated, then data scientists feel more comfortable in the work they are doing.
4. Provide the necessary tools
If you want to keep high-quality talent, you need to give them high-quality tools to work with. According to the study, data scientists expect to have access to the latest tools and techniques in their field. The report found that data scientists were statistically happier in jobs that provided the latest technology.
Companies that are using data for purposes like AI training should probably keep that information fairly updated anyway, Loucks said. Regardless, business executives need to provide the tools necessary to get useful results.
Affirmation and recognition are necessary for data scientists. While being paid well is important, these professionals especially value when their work is recognized by managers or peers. Job satisfaction statistically increases for data scientists who are praised for their work, according to the study.
"They respond positively to being recognized in their job title for the level of responsibility they have," noted Loucks. "So even something like recognizing them through a job title upgrade can help make them feel more satisfied in their jobs."
Macy Bayern has nothing to disclose. She does not hold investments in the technology companies she covers.
Macy Bayern is an Associate Staff Writer for TechRepublic. A recent graduate from the University of Texas at Austin's Liberal Arts Honors Program, Macy covers tech news and trends.