We’ve all heard it – it’s nearly impossible to pry away top data scientists to join your team. It’s an exaggeration, but it’s generally true that top data scientists are already in a very comfortable position with a team that’s doing very interesting things. How can a company, especially one that might be smaller and with fewer resources than the tech giants, realistically compete?
The market of data science jobs is, unfortunately, still dominated by buzzwords. -Dima Korolev
First off, the situation isn’t necessarily that dire. Assuming you’re willing to pay at least market rate, data scientists are generally most interested on the type of work they’d be doing, versus the brand name of the company.
Not an Impossible Task
As a smaller company, you’re likely already in a high-growth potential area, maybe riding on a trend that could be huge within the next few years. This is this the stuff that data scientists really care about – as long as it’s conveyed properly.
In terms of describing the role to a prospective hire, don’t just focus on the growth of the company or team. Sure that’s impressive, but that’s also there in probably 90% of the pitches we hear from recruiters.
What’s much more important is making it very clear exactly what my role could be in helping with that growth – how exactly can I expect to contribute and grow with the company? What will my day-to-day look like, and what type of direct career progression can I expect as the company grows?
In what specific area will I be helping with, and how exactly is that linked to the growth of the company?
What Keeps Them Passionate
Additionally, one of the core qualities of a top data scientist is curiosity – what hidden relationships will they find in the data that could have huge real-world impact? After a few years at a company, some data scientists will start to feel that they’re getting a bit of diminishing returns in their current role.
Financially they’re probably doing well, but intellectually they start to get a growing sense that something is lacking, and things aren’t quite as exciting as they used to be.
For data scientists, they are especially sensitive to that sense of excitement. It’s what drives pretty much all of us, and when that passion starts to fade, it’s a huge driving factor for looking around for other opportunities. Especially when we’re given the opportunity to get our hands dirty with fresh data sets that could be at the early stages of a huge growth industry – those are some factors which less-resourced companies should emphasize.
Sources of Growth
Again, this ties back to what specific role the data scientist would play in that growth. Mission is great and all, but unless we see a very clear link between the potential day-to-day and how that directly impacts the company’s growth, it’s hard to get the attention of top data scientists.
They already have all the stuff that you’re probably offering, and more – with the exception of getting in early as a key contributor/pioneer in a field that isn’t yet well-developed.
Any recruiting and outreach process for data scientists should start with a brutally honest assessment of how exactly your unfilled role compares with the rest of the market – especially from an intellectual perspective.
If you really feel stuck, reach out to data scientists you know (in a non-recruiting capacity) and discuss the job with them, and most of they will bluntly tell you what’s lacking in your pitch, and simple tweaks to make it more effective – and if you have no data scientist friends, feel free to reach out to me.
In other words, the iterative process of getting (and being receptive to) real-world feedback could be more valuable than some hiring managers assume.