A global travel technology company is seeking a Machine Learning Science Graduate for a PhD role starting in 2026. The successful candidate will engage in innovative projects involving statistical methods and machine learning techniques to improve the travel experience. The position offers a hybrid working model, competitive salary of £70,000, and a variety of benefits including travel discounts and insurance options.
Expedia Group brands power global travel for everyone, everywhere. We design cutting‑edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.
To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated, and when one of us wins, we all win.
We provide a full benefits package, including exciting travel perks, generous time‑off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey.
Travel is so much more than simply reaching your destination. Along the way you will make an immediate impact on reimagining the way people search for travel with our awesome team by inventing brand‑new techniques to power global travel for everyone, everywhere. From building pipelines and prototyping new ML models with A/B testing, to applying new techniques to services that run tens of thousands of requests per second, there is no shortage of opportunities for technical innovation at Expedia Group – the sky’s the limit!
Applying statistics methods like confidence intervals, point estimates and sample size estimates to make sound and confident inferences on data and A/B tests
Applying Natural Language models to Google keyword analysis and applying meta models to our multi‑objective ranking problem
Communicating complex analytical topics in a clean & simple way to multiple partners and senior leadership (both internal & external)
Conducting feature engineering and modifying existing models/techniques to suit business needs
Developing domain expertise in fraud & risk to understand how to detect risky transactions
Modeling rich and complex online travel data to understand, predict and optimize business metrics to help improve the traveler experience
Framing business problems as data science problems with a concrete set of tasks
Apply your domain (i.e., travel, online retail) knowledge, business acumen (understanding the underlying business objectives), and critical reasoning skills to your work
Must be available to start in 2026
Must be graduating between 2025 and July 2026 with a PhD degree in a technical or analytical‑related subject such as Computer Science (with focus in areas like Artificial Intelligence, Machine Learning, Natural Language Processing, Data Mining, Data Science), Mathematics, Physics, Statistics, Operations Research, Electrical & Computer Engineering
Must be willing to relocate to city of job location if outside commuting distance
Helpful to understand ML techniques like Regression, Naïve Bayes, Gradient Boosting, Random Forests, SVMs, Neural Networks, and NLP
Helpful to have experience with programming, statistical, and querying languages like Python, R, SQL/Hive, Java
Helpful to understand distributed file systems, scalable datastores, distributed computing and related technologies (Spark, Hadoop, etc.); implementation experience of MapReduce techniques, in‑memory data processing, etc.
Helpful to be familiar with cloud computing, AWS specifically, in a distributed computing context
Helpful to be able to effectively communicate and engage with a variety of partners (e.g., internal, external, technical, non‑technical people)
70,000 GBP salary
Hybrid work policy
Travel discounts
Medical, dental, and vision insurance options
Travel and wellbeing reimbursement
Restricted Stock Units
Apply now! Our dedicated early careers team will review your application and suitable applicants will be encouraged to complete an immersive strength based online assessment as the first step. Depending on the role profile you are applying to, selected candidates may also be asked to take a skills‑based screening assessment. Candidates who are invited to a final round interview will have the opportunity to meet with members of our team through two virtual interviews covering both technical and behavioural skills related to the position.
If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.
All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.