A Risk Assessment for Your ML/AI Job Security

Companies are cutting costs due to the economic uncertainty triggered by the COVID-19 pandemic. This has led some data professionals – data engineers, data scientists, ML engineers, and so forth – to question their job stability. And with good reason.

It’s not just that employers may cut headcount across the board to save money; it’s that many of them over-invested in the data hype, so their data teams may become an easy target for downsizing.

Is your data job secure? While I can’t tell you for ceratain, I can offer some thoughts to help you gauge your risk.

A risk assessment, in three questions

The thought of losing one’s job can be a scary prospect. Doubly so when it happens during a wider economic downturn, because that can make it tougher to find the next job. This is why you want to take a dispassionate, objective look at your situation to reduce your uncertainty. Doing so will help you plan your next steps and get ahead of potential problems.

The three biggest factors affecting your state of employment in a company are the company itself, your team’s role in that company, and your role in your team. We’ll evaluate them in that order.

Give yourself one point for each “yes” to the following questions:

1 - Is your employer doing well, overall?

Some companies have healthy cash reserves and/or solid revenue streams that will help them weather the storm. A handful of them may even benefit from the shifting economic conditions. And this isn’t just a matter of company size, either. Even a smaller business, under the right circumstances, can survive and thrive in this climate.

That’s not to say that these companies won’t engage in any belt-tightening. But there’s a difference between “the company is more cash-conscious right now so we’re keeping an eye on things” and “we were already skating on thin ice so we need to quickly slash budget wherever possible.”

If your company is in that former, healthier group, give yourself a 1 here.

2 - Is your company making good use of ML/AI?

Some companies have found ways to integrate data collection and analysis into their business – that may even be the core business – so they have a clear picture of how ML/AI helps the company achieve its goals. They also have a good understanding of what data does, and have possibly developed a formal data strategy to guide them. If this describes your employer, they clearly need ML/AI to keep the company going, so it’s unlikely they’d wind down your team. Give yourself a 1 here.

Other companies built their data teams on shaky decisions, and it shows. I’ve met my share of data professionals who didn’t feel they were providing much value. Some went as far as to question why their company had hired them in the first place. These jobs are at greater risk of being cut, since there’s no clear connection between the company mission and the work the ML/AI teams are doing.

3 - Do you have deep, well-rounded ML/AI experience?

A healthy company with a clear and realistic need of ML/AI may still need to shrink the data team to cut costs. Practitioners with deep, well-rounded experience stand a better chance of sticking around. They’ve developed a good nose for tools and techniques, which reduces the time (ergo, budget) they spend sorting out how to address a new data problem. They also know more than just algorithms, which makes them flexible and independent: they can pull their own data, deploy their models, and otherwise handle the full lifecycle of a data product.

If this describes you, congratulations. Give yourself another 1.

Entry-level data scientists may have more trouble here. They are less efficient than their more-experienced counterparts and also demand more of that group’s time for support and guidance. This is fair and to be expected – they’re still learning the ropes, after all – but it nonetheless means their jobs are at greater risk of being cut when money is tight.

Add up your points, and …

These three questions covered the big-picture criteria that a reasonable employer would weigh in their layoff decisions. Adding up your points will provide a rough idea of your chances of surviving budget cuts and restructuring: if you scored a 2 or 3, things are looking pretty good.

That said, your score is not a gauge of whether your job is at risk, but how much it might be. If your employer is not reasonable, or if they’ve considered other factors beyond those three questions, even a strong 3 can face layoffs. When it comes to jobs, then, it’s best to keep your eyes open and be open to new opportunities.