Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and implement machine learning models for personalised recommendations.
- Company: Global travel tech company based in the UK with a focus on innovation.
- Benefits: Competitive salary, diverse team, and opportunities to impact the travel industry.
- Why this job: Join a dynamic team pushing the boundaries of technology in travel.
- Qualifications: Ph.D. or Master’s in a relevant field and strong Python programming skills.
The predicted salary is between 36000 - 60000 £ per year.
A global travel technology company based in the UK seeks a Machine Learning Scientist II. In this role, you will develop and implement machine learning models for personalized recommendations and collaborate with cross-functional teams.
Candidates should hold a Ph.D. or Master’s in a relevant field and possess strong programming skills in Python.
This position offers a unique chance to impact the travel industry's innovative solutions. Join a diverse team pushing the boundaries of technology and travel.
ML Scientist II — Scalable Personalization & Recommendations in London employer: Expedia, Inc.
Contact Detail:
Expedia, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Scientist II — Scalable Personalization & Recommendations in London
✨Tip Number 1
Network like a pro! Reach out to people in the travel tech industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to recommendations. This will give you an edge and demonstrate your expertise.
✨Tip Number 3
Prepare for technical interviews by brushing up on Python and machine learning concepts. Practice coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace ML Scientist II — Scalable Personalization & Recommendations in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in machine learning and programming. We want to see how your skills align with the role, so don’t be shy about showcasing your projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about personalised recommendations and how your background makes you a perfect fit for our team. Let us know what excites you about this opportunity!
Showcase Your Technical Skills: Since strong programming skills in Python are a must, make sure to mention any relevant projects or experiences that demonstrate your expertise. We love seeing practical applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Expedia, Inc.
✨Know Your ML Models
Make sure you brush up on the latest machine learning models, especially those related to recommendations and personalisation. Be ready to discuss your previous projects and how you implemented these models, as this will show your practical experience.
✨Showcase Your Programming Skills
Since strong programming skills in Python are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to feel confident during the interview.
✨Understand the Travel Tech Landscape
Familiarise yourself with the travel technology industry and the specific challenges it faces. This knowledge will help you tailor your answers and show that you're genuinely interested in how your work can impact the sector.
✨Collaborate and Communicate
As you'll be working with cross-functional teams, highlight your teamwork and communication skills. Prepare examples of how you've successfully collaborated with others in past projects, as this will demonstrate your ability to fit into their diverse team.
