Product Manager - Product Data

London, England, United Kingdom · Supply


About Lyst

Lyst is a Global Fashion Search Platform which connects millions of shoppers globally with the world’s leading fashion designers and stores, giving them a simpler, more engaging buying experience.

At Lyst we work in squads - small, self-managing, autonomous teams with end-to-end responsibility for a specific customer-focused project. This structure brings together Lysters from all the disciplines that are needed to deliver the squad’s goals. We reward these squads for the impact they make and value the innovative approaches that autonomy and alignment can bring. We hire great people and get out of their way.

The Role

Within Lyst, the Supply tribe is responsible for working with retailers. Within Supply, the Product Data team is directly responsible for collecting, processing, and cataloging the products offered by various retailers.

Here at Lyst we're aiming to surprise and delight our users constantly with a great experience that keeps them coming back for more. To help us continue to build this experience, we're looking for an experienced Product Manager to help find new opportunities to continuously improve our integrations with partners and the product data we receive. The ultimate aim is to provide customers with the information and context they need to make informed purchase decisions and come back to Lyst again and again.

You will take responsibility for the creation and delivery of the strategy for your product area, to define and deliver high performance digital experiences.

The importance of this position and freedom that comes with it is fairly exceptional and you will receive high level of support from VPs, as needed, to help execute your strategies in the most effective way possible.

The Product data squad consists of a team of engineers with differing levels of expertise and skill sets and their mission is to ingest and provide fresh and accurate inventory data to customers.

We require someone who is interested in working with data pipelines and appreciates the complexities of these environments when dealing with multiple APIs and millions of data points per day.



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