Data Scientist

About Skyscanner

Everyone loves travelling, but planning is not without its challenges. That's why we've spent 20 years building tools that turn travel-planning chaos into a breeze. Today, around 160 million travellers count on us every month to skip the whole “47 browser tabs open” phase and find flights, cars, and hotels quickly and easily.

Joining Skyscanner means becoming part of a global brand that's striving to become the planet's go-to travel hack accessible for all.

Our vision? To be the world's number one travel ally. (Ambitious? Yes, but, hey, that's what got us here.)

About the role
(Hybrid)

• Building smarter recommendation systems: You’ll join the team behind the ML systems that help millions of travellers find the right hotel or rental car — and you’ll keep raising the bar on relevance, quality, and performance.
• Owning the full journey: From fuzzy product questions to crisp modelling goals, you’ll run initiatives end-to-end: define what “good” looks like, build models, ship them, and iterate based on what the world tells us.
• Working where it matters: You’ll partner closely with Product and Engineering to get production systems into travellers’ hands (not just into notebooks).

What you’ll be doing

• Improving ranking & recommendations: You will design, build, and iterate on production ranking and recommendation systems across Hotels and Cars.
• Turning ambiguity into objectives: You will translate open-ended product challenges into clear modelling goals and hypotheses.
• Defining meaningful success: You will set success metrics that balance user value with marketplace and business outcomes.
• Running rigorous evaluation: You will design and analyse online experiments and offline evaluations to understand real impact.
• Applying statistical & causal reasoning: You will use strong statistical foundations (and causal thinking where it counts) to make confident, responsible decisions.
• Shipping with partners: You will work hand-in-hand with Product and Engineering to deploy, monitor, and improve systems in production.
• Communicating to influence: You will explain complex trade-offs clearly and help shape roadmap decisions with evidence.

About you

• Production-tested: You have 2+ years’ experience as a Data Scientist working in a production environment.
• Applied ML experience: You’ve worked on real-world machine learning or applied data science problems (bonus points if you have worked on ranking/recommender problems).
• Strong fundamentals: You bring solid foundations in statistics, machine learning, or quantitative analysis, and, you know when to use which tool.
• Hands-on with Python & SQL: You’re comfortable building in Python and querying data with SQL.
• Team-friendly engineer mindset: You’re familiar with collaborative development practices like version control and code review.
• Structured problem-solver: You can take an ambiguous problem, break it down methodically, and move it forward without needing a perfect brief.
• Thoughtful evaluator: You care about robust evaluation, including fairness and reliability considerations.

What it's like here

We are the real deal — no corporate gloss, no empty promises. Just a team of genuinely curious, caring humans, building things that help travellers explore the world a little easier.

Skyscanner is made up of brilliant humans from every corner of the world. We believe travel makes the world better - and that the same is true of our diverse teams. We're proud to be an equal opportunities employer and are committed to building an inclusive workplace where everyone can thrive and products that are accessible to all.

Sound like your kind of adventure? Apply now and help us shape the future of travel.

We're committed to ensuring our application and recruitment processes are inclusive and accessible to everyone. If you require any reasonable adjustments or accommodations for interviews, and/or wish to apply under the Disability Confident scheme, please let your recruiter know. If you’d like more information on any of our policies, such as hybrid working or Parental Leave policies (typically we pay a minimum of 24 weeks birth parent/maternity leave globally), our recruitment team can provide more information on these.