Skyscanner is a leading global travel search site and app, a place where people are inspired to plan and book direct from millions of travel options at the best prices. We employ over 1000 staff across 11 offices globally, and, having reached market leader status, we were recently acquired by Chinese online travel company Ctrip in a deal valued at £1.4bn. While we remain operationally independent, our acquisition by Ctrip allows us to take the business to the next level of accelerated global growth. It’s a hugely exciting time for Skyscanner and the over 80m people who use us every month. We are unbiased and free, and our secret is in our unique proprietary technology that connects people directly to everything the travel industry has to offer.
At Skyscanner, we are organized into squads (cross-discipline teams which execute against a specific goal) and tribes (logical groupings of squads). Data scientists work in a distributed manner across the business solving challenging projects like new product features/improvements, discovering insights from data and building a world class platform to deliver machine learning solutions at scale. Data Scientists at Skyscanner are working on exciting projects such as hotel and flight ranking, destination discovery using image recognition, using models to speed up flight search across 1000+ partners, among many other data rich projects.
You can expect to formulate ideas, develop prototypes and work with engineers to implement models in live production systems that impact tens of millions of travelers around the globe.
The role will include:
- Process large amounts of data from multiple sources and extract relevant insights.
- Research new ways of modeling data for actionable insights and product improvements.
- Perform statistical analyses and build machine learning solutions to support Skyscanner product and business needs.
- Partner closely with product, engineering and growth to solve quantitative problems and identify trends and opportunities
- Design agile and rigorous experiments to measure effectiveness of models, tools and programs.
Some of our expectations for the role include:
- You can communicate clearly with both technical and non-technical colleagues. You accurately judge the level of detail required in different situations.
- You’re comfortable with Python and/or R
- You have worked 5+ years in a data science/analytics role
- You enjoy working in a dynamic environment with teammates from a variety of disciplines.
- You can manage multiple stakeholders and priorities
- You are able to identify and scope out new opportunities for data science work to positively impact Skyscanner product and vision
- You are happy to work independently and in a self-guided manner
What else can we offer you……
We are proud to have a working environment that sets our employees up for success, as well as all the usual perks such as barista coffee, fizzy & fresh drinks, fresh & dried fruit, veg, hummus, popcorn and we can help with ‘down-time’ in the office that includes table tennis, pool table, foosball, xbox, office scooters, and massage chairs. We also provide for your health with medical insurance, health screening options, gym membership, headspace subscription and an employee assistance programme to support you and your loved ones. Then it gets really interesting, and you can buy more holiday, donate to a good cause, take part in 2 hackdays per year, and 1 charity day, work from your home country for up to 3 weeks, spend up to 30 days working from another of our offices globally. You also have the option to take part in our extended annual leave which is an additional 3 weeks’ break (unpaid) after 3 years’ service or take 5 weeks’ break (paid) after 5 years’ service.
Join us now.For more details on Engineering at Skyscanner you can check our Engineering Blog and follow Skyscanner Engineering on Twitter
- - ‘Skyscanner University’ offers a range of courses for tech and business topics.
- - At Skyscanner there’s no clocking in and there’s no bell at the end of the day, they prefer to give you the freedom and autonomy to do your job, add value and own your work.
- - Better than average annual leave in all office locations.
- - There’s enhanced maternity and paternity leave and a flexible working policy to encourage and enable a healthy work-life balance.