Even low-profile companies can offer exciting data science work. Data scientists want to feel that leaders respect their work as a core business function. They want to know how their work will affect the business and customers. They want to be challenged with ambitious, cutting-edge projects and know that they have the resources and support they need to tackle them.
I prefer interesting projects [over interesting companies]. An interesting project could mean something more because it could have more impact. I prefer the interesting projects because I’m going to feel satisfied.”
Lead AI Scientist, Target
Every day, executives at traditional companies complain that they can’t compete for data science talent with Google, Meta, Apple, and Amazon.
Our response: nonsense! You can compete and win.
Nearly 40% of data scientists we surveyed described working for a legacy (non-tech) company as “very or somewhat appealing.” Lots of people don’t want to work at a big tech companies. The reasons they cite include ethics, cultural mismatch, or lifestyle.
I knew I wanted to work in a meaningful situation, something that really had a positive impact on people’s lives, which is why I really like working in healthcare.”
Data Scientist, Amgen
In the era before AI, you were in control. You were buying a job, and the talent was selling labor. Supply outstripped demand, and you had choices. Your new strategy must start by accepting that the talent is now in control.
In this new situation, you’ll need to sell your company’s unique AI opportunities. Emphasize how potential hires can positively affect society. Industries like healthcare, insurance, banking, and manufacturing all make people’s lives better.
Also sell the opportunity to transform your company. For example, imagine a prospective hire who’s considering an opportunity with either your company or Facebook. Here’s what you could say:
I’m just saying the S&P 500, 10 to 15 years from now, yes, it would be important to have a great digital experience with machine learning and personalization evolves. But the leadership probably isn’t there. . . . The leadership doesn’t realize how critical [infrastructure investment] is to being successful four or five years from now.”
Senior Data Scientist, Nike
Skip the bravado. Every company claims to be data-driven. But very few are. Even the tech giants have stovepipe systems, disconnected data, and a suboptimal development environment. However, these companies attract talent because they recognize the challenge and invest to make their data scientists successful. Investment signals how well an employer values data science.
You can follow the same pattern. If your competitors make unrealistic claims about their current capabilities, distinguish yourself by speaking the truth.
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