Case Studies

Last week, we shared some insights from our data science and data engineering recruiting teams on how the Great Resignation is impacting the current hiring market. This year we’ve seen fewer data scientists on the market since many changed jobs in 2021, increased hiring leading to more open opportunities, and the increased focus on other factors like remote work, hybrid schedules, and company culture.So how can teams looking to hire data science or data engineering talent address some of the hiring challenges that the Great Resignation is spurring on right now? Based on our previous research and insights from our recruiting team, we wanted to offer a few suggestions.

Reducing Impacts from the Great Resignation on Data Science & Data Engineering Teams

1. Build strong relationships among your data team

Positive relationships can go a long way towards retaining employees, including managing relationships between you and your data team, as well as fostering camaraderie within the team. Strong communication, transparency, and offering mentorship can all build stronger relationships between leadership and the team. For early career employees especially, focusing on team-building or fun activities can build stronger cohesion within the team, which can help make employees less likely to be tempted by other job offers.

2. Establish partnerships with schools to hire early career data professionals

Many data-focused programs are open to working with employers because they’re looking for industry professionals to either help guide the curriculum, contribute judges for a hackathon or sample datasets, or offer services like resume reviews. This is a great way to establish a quality pipeline of new talent and get your company name out there. Working with students can also provide ample opportunities to see how they work, introduce them to practical tools, and even serve as a sort of extended interview process for students that you may want to hire upon graduation or for internships. This could include institutes or programs, and you can also look into partnering with student-run organizations as well.

3. Emphasize broader impact and business value

Data scientists and data engineers want to feel that their work is making a difference at their company. They are much more motivated to work on projects when organizations are eager to accept their insights and solutions, and are willing to make tactical, functional, or strategic adjustments according to findings. According to reports from Gartner and Dimensional Research, the success rate for data science projects is shockingly low. This means companies must work to deliberately enable analytics and create a positive culture toward data inspired decision making. Work to create an environment where analytics are appreciated, accepted, implemented, and a part of business decision making, and also provide your data talent priority projects that have a real impact on business objectives.

4. Build up or train citizen data scientists for some roles

There are several ways to build up internal talent for data science or analyst roles, which can include things like encouraging certifications, setting up internal training opportunities, or forming a hackathon. There are several different forms of certification options depending on what makes the most sense for your needs, such as tool-based (Python, R, etc.), technique-based (NLP, computer vision, etc.), or knowledge-based (evaluating how someone understand the concept of data science, etc.), which can help jumpstart internal talent for more data-oriented roles. Internal hackathons can also be a great way to identify aptitude and gauge interest in data science from employees in other areas of the business.

5. Cultivate your company culture

As we mentioned in our previous blog, more data professionals are relying on sites like Glassdoor to evaluate employers before continuing the interview process. We recommend focusing on the positive aspects of working for your company and working with your current data team to address their concerns.

6. Plan for attrition by continuously recruiting

Even if your team is fully staffed, it’s important to keep long-term plans in mind, and that includes planning for attrition. Hiring opportunistically can help you stay out in front of market trends by keeping an eye out for available talent before you are facing a shortage.

7. Develop career paths for your data talent

Data professionals value career advancement and learning, which can include promotions, but also expanding their capabilities and broadening knowledge. Investing in your data talent and giving them opportunities to learn and expand their skillset can benefit both business goals as well as employee retention.

8. Evaluate compensation

Our research found that data professionals who changed jobs were receiving significant salary increases, so be sure that you’re aware of current market rates if you wish to retain key staff. We’ve also seen some data teams employing the use of preemptive retention bonuses, spot bonuses to recognize work on key projects, and even salary increases outside of the normal annual schedule.

9. Maintaining long-term relationships even after employees move on

As we mentioned in the first bullet, building strong relationships with your team is important, and this can include staying in touch with them after they leave. Especially with the hiring market undergoing such monumental shifts in terms of remote work, hybrid schedules, and other factors, the climate may be much different in 18 months compared to today. Employees that return will already have built-in industry experience, and some may find that if they took a remote opportunity, they may miss the in-person experience and prefer at least some face-to-face interaction. This can be especially important if your hiring needs are geographically specific.Our 2022 data science & analytics salary report will be coming out in just a few months, so it will be especially interesting to see how the Great Resignation has impacted salaries compared to last year, and what other trends have developed. We look forward to sharing more data and insights with you soon!