Uber cut hiring by 18% a month before layoffs
Yesterday, Uber ($NYSE:UBER) laid off 435 people from its product and engineering teams, representing about 8% of its workforce, as reported by TechCrunch. But ahead of that announcement, hiring at the company — and specifically in the divisions affected by layoffs — saw a dramatic cut in early August.
On or around August 4, openings at Uber sunk from 1,530 to 1,290 in the space of just a few days. Since then, openings at the ridesharing company have slowed even more, to around 1,260.
The pattern is common: layoffs are often preceded by slowdowns in hiring that foreshadow the types of positions about to be cut. In this case, hiring dropped in early August across the company's Design, Product Management, and Engineering categories. Meanwhile, hiring in the company's Sales, Business Development, and Community Ops divisions remained flat or up.
Uber's Engineering division saw the most dramatic slowdown in hiring, with openings nearly halved in early August. Product Management openings also saw deep cuts, along with Design and Backend.
Openings for Community Operations professionals remain healthy, and even increased a bit in early August as other divisional hiring was slowed. That pattern was similar for both Business Development and Sales.
Community Operations remains the most in-demand department at Uber, outpacing even Sales and City Operations. Community Operations is described by Uber as the "organization responsible for building [its] customer service network."
The inconsistent cuts reflect a company focused on generating revenue as opposed to product in the shadow of disappointing earnings as a newly public company. Meanwhile, the company's employee count — according to LinkedIn data, which includes everyone from executives to drivers — continues to climb.
Meanwhile, a new California law will require Uber (along with other gig economy businesses like Lyft and Doordash) to treat its drivers as employees rather than contractors.
About the Data:
Thinknum tracks companies using information they post online - jobs, social and web traffic, product sales and app ratings - and creates data sets that measure factors like hiring, revenue and foot traffic. Data sets may not be fully comprehensive (they only account for what is available on the web), but they can be used to gauge performance factors like staffing and sales.