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Founders Factory Address: London, UK
If you're a data scientist with a proven track record of deploying AI and/or ML in a production environment, this is your opportunity to join a real rocket ship. We’ve secured funding and are about to commence raising our next round, you’ll have total control to build against our vision and we’re an industry recognised disruptor of the travel space being featured by the likes of Skift, The Guardian, The Telegraph and Lonely Planet. Get on board!
BRB’s goal is to make travel something you experience, not something you plan. In August 2018 we launched as the world’s first travel subscription platform; providing our customers 3 short breaks a year for a monthly fee.
We looked at the last 20 years of innovation in the travel industry and realised nobody had tackled the most painful part of travelling - actually booking it. With BRB we strive to make it possible to book your next getaway in 60 seconds, so all our customers need to do is turn up at the airport and start their adventure. We’ve been highlighted by Skift as one of the top startups to watch in 2019, featured on CNBC and written about in major publications like the Guardian and Telegraph.
With a fast-growing user base of customers excited for their next adventures with us. Our goal is to revolutionise the way millennials engage with travel, by making it social, mobile and effortless. We fundamentally believe seeing more of the world shouldn’t be a black hole in your monthly budget, or a full-time job to organise.
We have a working product in market and strong traction. The next stage of our growth is to create a leading recommendation engine for the travel industry. We have the ability to gain more data points on each customer than any other traditional travel provider in the industry - leaving open the opportunity to create a new class of recommendation systems for customers and our in house team of travel bookers - that's where you come in!
We want you to work with us to build a system that can understand customer profiles and match them to destination cities - and in future hotel products and in destination experiences. This system should be able to be accessed via an API - consuming data from various sources and returning answers in a JSON format.
What does this look like in practice?
We want to build the world's best matching algorithm between people and travel products. At its simplest level, imagine:
1. Customer A comes through our website and signs up, providing us with a number of data points. We then build a fingerprint of that customer and a complex profile of their interests and match that to complex profiles of cities. We then learn that Customer A loved their trips to cities X and Y but weren't so keen on Z.
2. Customer B comes to the site with a similar profile to Customer A - we still send that customer to cities X and Y but this time we substitute city Z for a new city, Customer B has a way better time, and future customers with that profile have an optimised pathway through BRB.
3. We start to expand this recommendation system from Customers <> Cities to Customers → Cities → Hotels → Experiences.
4. We layer third party data to create unique opportunities. Imagine how cool it would be if we sent you to a city that your favourite band is playing in because you connected your Spotify Account. Or arranged an automatic room upgrade and a bottle of champagne because we know from Facebook that it's your anniversary weekend.
To achieve this we know we need to gather more in depth knowledge of our customers - what data points should we be gathering, how should we be gathering them? Where should we get data to build our city profiles? What's the relevant information - population densities? Number of mountains? Number of live music venues? All of it can be used to generate unique properties that make for an incredible data set that isn't being explored by any of the agencies in the travel market. This is your opportunity to explore data opportunities in the travel space and build world-class algorithms that other companies would struggle to build because of their transactional relationships with customers.
What technologies / frameworks will be needed?
Published on: Dec 5, 2019
Expires on: Mar 5, 2020
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