Spate is the machine intelligence platform used by top industry beauty brands. We analyze over 20 billion search signals to spot the next big beauty trend and help brands develop their marketing/product strategies.
Spate is looking for a backend engineer to help us design and implement the next iteration of our data pipeline, storage, and API backing our SaaS platform.
Responsibilities:
This is a technical role with a high degree of autonomy expected.
Minimum Qualifications:
Preferred Qualifications:
Why Spate?
Join a well-funded company that is working with the top brands in consumer goods
Work directly with the founders to set the direction of the company
Compensation --> €70k to €80k, depending on experience
Paid Time Off (Vacation, Sick & Public Holidays)
Always be up-to-date on the latest trends!
We enjoy a casual atmosphere, but our culture is about getting things done. We are passionate yet pragmatic when it comes to solving problems in a fast-paced environment. Our standards are high, but we thrive on working with people we respect and can learn from. We’re flexible on work styles, as long as everyone is getting their work done - and getting it done well.
About Spate:
At Spate, we use data science to predict the next big consumer trend in beauty, personal care & food.
Spate was founded in 2018 by Yarden Horwitz & Olivier Zimmer, two ex-Googlers who led the trendspotting division at Google and uncovered trends such as turmeric, cold brew, and face masks. Spate has been funded by the prestigious Y Combinator incubator and Initialized Capital. We currently have ~90 clients in the U.S., mainly in the beauty space from direct-to-consumer brands to big names such as L’Oréal, Estée Lauder, Unilever, etc.
As two ex-Googlers with a passion for using data to spot new patterns in consumer behavior, and we have made it our mission to build the world’s greatest consumer trends prediction platform of all time. And not just because we want to be trendy, but because we want to help brands get better at giving consumers what they really want.
Brands waste over $200BN every year due to product launch failures and inventory waste. By spotting Turmeric, we were able to tell brands to stop wasting money on kale products and provide consumers with glorious golden milk lattes instead - because that’s what consumers want.
How do we do this? We tap into publicly available consumer data (anonymous and aggregated) to identify interesting shifts in consumer behavior. We leverage the latest available technology in ML to solve problems in ways that have never been explored before.
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