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The market for data scientists is

completely bonkers.

Desperate hiring managers started calling us for advice

How can I compete with these tech companies?

“We finally found an awesome data scientist, but she took a job at Spotify; they offered her more than my boss makes.”

Should we start offering four-day work weeks?

“I finally got my HR department to agree to hire remote data scientists, but I still can’t find anyone! Competitors offer remote work and pay top-of-market salaries.”

How do we attract and retain the data scientists we need?

“I asked my data scientist to focus on solving our business problems. He told me he prefers to do experiments, and he quit on the spot.”

How can we create an environment where data scientists want to work?

“Our top project is stalled because our best data scientists resigned in Q1. We were shocked to learn that all of our data scientists are unhappy; our IT team likes our work.”

We commissioned a study to help you understand how the most successful AI leaders are winning the fight for data science talent.

We started by surveying more than 100 data scientists about what they want from their careers. We did qualitative interviews with many others and compared our findings to what we learned from the companies that are becoming talent magnets. This report compiles those results and provides recommendations to help you apply the strategies for success in your own company.

This exclusive report includes:

Our top 10 recommendations, all supported by survey data.

Insights into the unique work of data scientists.

Tips for becoming an employer of choice.

Tactical advice for improving your recruiting and retention.

After reading the results of Prolego’s data science talent study we rewrote our data science job descriptions. We saw an INSTANT increase in the quality and quantity of candidates. It took us less than an hour to make the changes. I now realize we were setting money on fire by promoting a sub-optimal job description and wasting time interviewing the wrong people.      

Feedback from an early reviewer