While many aspects of our lives haven’t fully returned to the pre-COVID-19 normal yet, the analytics and data science job market is perhaps even stronger now than it was two years ago. Not only are a lot of jobs being posted, but those jobs are being structured in such a way that makes them appealing to a broader range of potential candidates. In this blog, I’ll cover a couple of aspects of today’s job market that every manager and job seeker in the field of analytics and data science should be aware of.
Flexibility is a Necessity, Not A Perk
Employees and candidates today demand flexibility. Period. Most of the people I’ve talked to, even those at very “old school” companies, expect flexible, hybrid work environments to continue permanently post-pandemic. There never was a good reason why getting work done required every person to be in the office every day. People like me who have successfully worked in a partially remote setting for years already knew this, but the pandemic has irrefutably proven it to be true to everyone willing to face the facts. Companies that push for analytics and data science employees to be onsite full time (or close to it) will hemorrhage talent. There are too many data science opportunities out there to expect candidates to settle for a role that lacks flexibility.
A fully remote workplace has its own pitfalls, too, however. A VP at one large company told me that when they surveyed employees to ask if they would prefer a fully onsite, a fully remote, or a hybrid work environment, the vast majority voted for a hybrid. People still want the ability to meet with their peers face-to-face. They just don’t want to be forced to do it every day. Think especially of people who are still early in their career. They may be living alone in an apartment and don’t have a lot of connections or knowledge of how their company works yet. Working from home all the time can lead to an isolated, depressing existence . It is wise to provide these employees the chance to get out of their jail cell (I mean apartment), get to know their peers, and learn how the organization works. Add some new traditions into the mix such as official group lunch days or happy hours as well. Let people have flexibility while continuing to give them opportunities to interact in person.
Swift And Decisive Action Is Required
There are stories all over the news these days about nice homes receiving multiple bids and selling above asking price within days. The only way to land a house is to act quickly and to submit competitive bids. The same is true with analytics and data science talent today. The really good people everyone wants to hire are getting snapped up quickly. If you expect to land your favorite candidates, you can’t afford to follow the classic 4-to-6-week interview process with multiple rounds of interviews that often leaves candidates in the dark about their status for days or weeks at a time.
In a discussion with a group of executives from multiple companies, one leader said that his organization is now making verbal offers on the spot before an interview ends if they really like the candidate. Another executive said that while they don’t make on-the-spot offers, they lock down specific next steps before ending any conversation. If another discussion is required, for example, it is scheduled before the current discussion ends. This way, the candidate is never left wondering what the status and timeline is. Obviously, the salaries offered must be competitive too, but you can lose a lot of candidates before they ever see your salary numbers if you aren’t moving fast enough and communicating your interest immediately.
More Than Ever, Don’t Compete on Salary Alone
Competing primarily with high pay is a dubious strategy even when you can afford it. In today’s environment, the desire of employees to have flexibility means that you can get rewarded by competing with non-monetary policies that don’t break your bank. During the same group discussion mentioned previously, several tactics being pursued included:
- One company’s data showed that employees who make it to the 3-year mark are much more likely to stay for a long time. As a result, they put in place retention bonuses that pay out over time instead of up-front signing bonuses.
- Another company was exploring not only providing flexible work locations, but also allowing employees to choose a 4x10 workweek instead of the classic 5x8 workweek. Granted, few data scientists work only 40 hours, but the concept does appeal!
- Yet another company was targeting smaller cities where the wages they could afford to pay were considered generous instead of targeting bigger cities where the pay wouldn’t cut it. Then, they let the candidates stay where they are if they take the job.
One big downside to these trends is that companies in smaller, less expensive areas are suddenly competing with companies from big cities who can afford to pay much more. That can be devastating to companies centered in those areas. Time will tell how things eventually balance out, but in the short term, these trends appear to favor big companies and large cities over smaller companies and smaller cities.
Play To Win!
Rapid change is still occurring so continuously study the market and adjust to the trends you see on an ongoing basis. The good news is that employees are looking for flexibility and the ability to balance work and life, so it isn’t 100 percent about compensation for many. The bad news is that many people won’t take a job that doesn’t match their need for flexibility, no matter the pay. As a result, your organization is going to have to push its comfort limits in terms of the level of workplace flexibility you’re willing to offer.
To win today’s talent war, challenge yourself and your organization to be bold, aggressive, and holistic in your recruiting and retention strategies. Take the opportunity the pandemic has provided to reconsider your longstanding practices and assumptions. If you want to land the best talent, you’ll need to adapt to how the market is working today, no matter how uncomfortable that may be at first.
Originally published by the International Institute for Analytics