Machine Learning Scientist II

Traveltechessentialist
City of London
3 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Researcher

Applied Scientist II - Computer Vision

Applied Scientist II - Computer Vision

Forward-Deployed Data Scientist II

Data Scientist II

Data Scientist II

Machine Learning Scientist II

  • United Kingdom - London


  • Technology


  • Full-Time Regular


  • 10/22/2025


  • ID # R-98197



Overview

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.


Introduction to the team

Private Label Solutions (PLS) is the B2B arm of Expedia Group. We bring Expedia Group's innovative technology and distribution solutions to partners across the world. These businesses include global financial institutions, corporate managed travel, offline travel agents, global travel suppliers (like major airlines) and many more …


We are looking for a ML Scientist II to join the Private Label Solutions (PLS) Machine Learning Science. You will join a team that builds end-to-end ML solutions for various business problems, contributing substantial value for our partners and for EG. We embrace test and learn by continuously experimenting, analyzing and improving our algorithms which has helped the B2B business become one of the fastest growing at Expedia Group.


This applied scientist role will join our ML team at Expedia Group. This role offers a unique opportunity to work on diverse challenges and contribute to cutting-edge solutions that drive significant impact for the business. You will gain expertise in commercial acumen, engineering, analysis, and applied machine learning at scale.


This role requires an individual that has a solid foundation in machine learning and engineering, is passionate about driving meaningful impact whilst being mindful of the broader context in which their work sits, is comfortable with ambiguity and enjoys the challenge of tackling open ended problems.


In this role, you will:

  • Develop and implement ML models for a variety of business applications within Expedia Group’s B2B arm.


  • Contribute to building and enhancing end-to-end ML solutions, from data preprocessing to production deployment.


  • Design and run A/B tests and experiments to continuously improve algorithm performance.


  • Stay current with the latest ML techniques and contribute to the team’s technical capabilities.


  • Collaborate with cross-functional teams to translate business needs into technical solutions.


  • Communicate methodologies and results clearly to both technical and non-technical audiences and work across the tech stack to deploy models.



Experience and qualifications

  • You hold a Ph.D. (preferred) or Master’s in Computer Science, Machine Learning, Mathematics/Statistics, or a related field.


  • You have 2 years of industry experience applying ML to real-world problems (desirable but not required).


  • You possess a solid understanding of machine learning algorithms, statistics, and probability theory.


  • You demonstrate strong problem-solving skills, a quick learning ability, and enthusiasm for tackling complex challenges.


  • You are proficient in Python, with experience using PySpark and ML libraries such as scikit-learn, TensorFlow, or Keras.


  • You are familiar with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, GCP), and can effectively communicate technical concepts to non-technical stakeholders.



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.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.