Machine Learning Science Graduate - PhD - 2026 - London at Expedia Group

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

13 Feb, 26

Salary

70000.0

Posted On

15 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Natural Language Processing, Data Science, Statistics, Feature Engineering, Programming, A/B Testing, Cloud Computing, Python, R, SQL, Java, Distributed Computing, Fraud Detection, Risk Analysis, Data Mining, Business Acumen

Industry

Software Development

Description

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. Why Join Us? 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 know that 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. We’re building a more open world. Join us. In this role you will: 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 Minimum Requirements: 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 Preferred Experience: 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) What We Offer: Successful candidates will receive a competitive compensation package including comprehensive benefits and other perks, some of which are included below: 70,000 GBP Hybrid work policy Travel discounts Medical, dental, and vision insurance options Travel and wellbeing reimbursement Restricted Stock Units Next Steps: 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 behavioral skills related to the position. These interviews will also be a chance for you to learn more about us, too! Accommodation requests 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. We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50 Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age. Expedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. For more information, visit www.expediagroup.com. Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals to whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is lifeatexpediagroup.com/jobs.

Responsibilities

In this role, you will make an immediate impact on reimagining the way people search for travel by inventing brand-new techniques. You will be involved in building pipelines, prototyping new ML models, and applying statistical methods to enhance the traveler experience.