Customer Success Manager - Corporate
Senior Enterprise Customer Success Manager
Senior Enterprise Customer Success Manager - Paris
Technical Account Manager (EMEA)
We’re building the technology that helps retailers understand their customers and give each person a unique experience.
We collect hundreds of millions of data points from our client's websites and pipe them through our realtime data processing pipeline. We then surface the data in our products for our users to explore and act upon by serving back tens of millions of personalizations to enhance the sites.
Building and improving a range of innovative products and services that clients use to understand their visitors, personalise their visitors experiences, and see the impact of these changes. You’ll get to set the direction of what’s being built. There are no predefined technologies. Except JavaScript; which we love (but please, no semicolons).
Currently we’re using ES2016 (now better known as Babel stage 0), our teams are quite keen on React and Redux, and our web servers are mostly node.js.
Building and improving a range of innovative products and services that clients use to understand their visitors, personalise their visitors experiences, and see the impact of these changes. You’ll get to set the direction of what’s being built. There are no predefined technologies. Except JavaScript; which we love (but please, no semicolons).
Building and improving a range of innovative products and services that clients use to understand their visitors, personalise their visitors experiences, and see the impact of these changes. You’ll get to set the direction of what’s being built. There are no predefined technologies. Except JavaScript; which we love (but please, no semicolons).
We’re looking for a Data Scientist to join our Research team, to help us develop intelligent products around this data, and conduct cutting-edge research into consumer behaviour on the web.
This is a great opportunity to conduct real R&D around human behaviour. Our data collection tools store more than 1 billion data points every day. Overall, Qubit technology tracks consumer journeys leading to billions of pounds of online spending worldwide every year, for some of the largest names in online retail.
We’re looking for someone smart and motivated, with experience solving real data analysis problems with statistical and machine learning techniques. As part of our research team you’ll help to understand our ever growing dataset, working closely with other parts of the business to ensure our products are ahead of the competition.
Currently we’re using ES2016 (now better known as Babel stage 0), our teams are quite keen on React and Redux, and our web servers are mostly node.js.
Yes, we try and open source some of our stuff. We hope you’ll join us to help us ship more of this. Here are some of the projects we’re most proud of:
HAProxy auto configuration and auto service discovery for Mesos Marathon.
A flexible nested router.
A Javascript library for state management in React applications