At a Glance
- Tasks: Create cutting-edge ML models for personalised recommendations and improve ML solutions.
- Company: Join Expedia, a leader in travel technology and innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Collaborative environment with exciting projects and career advancement.
- Why this job: Make a real impact in the travel industry with your ML expertise.
- Qualifications: Ph.D. or Master’s in a related field and proficiency in Python and cloud platforms.
The predicted salary is between 60000 - 80000 £ per year.
Expedia, Inc. is seeking a Machine Learning Scientist II to join their B2B Machine Learning Science team. The ideal candidate will develop ML models for personalized recommendations and enhance end-to-end ML solutions.
This role involves:
- Collaboration with cross-functional teams
- Designing A/B tests
Requirements:
- Ph.D. or Master’s degree in a related field
- Proficiency in technologies such as Python, PySpark, and cloud platforms
ML Scientist II — Recommendations at Scale employer: Expedia, Inc.
Expedia, Inc. is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for Machine Learning Scientists looking to make a significant impact in the travel industry. With a strong emphasis on employee growth, you will have access to continuous learning opportunities and cutting-edge technologies, all while working in a vibrant location that encourages creativity and teamwork.
StudySmarter Expert Advice🤫
We think this is how you could land ML Scientist II — Recommendations at Scale
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Expedia or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving recommendations. Share it on platforms like GitHub and make sure to highlight your proficiency in Python and PySpark.
✨Tip Number 3
Prepare for those interviews! Brush up on your A/B testing knowledge and be ready to discuss how you've collaborated with cross-functional teams. Practice common ML interview questions to boost your confidence.
✨Tip Number 4
Apply through our website! We’ve got loads of resources to help you ace your application. Plus, applying directly shows your enthusiasm and commitment to joining the team.
We think you need these skills to ace ML Scientist II — Recommendations at Scale
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ML models and technologies like Python and PySpark. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
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 B2B Machine Learning Science team.
Showcase Collaboration Skills:Since this role involves working with cross-functional teams, mention any past experiences where you collaborated effectively. We love seeing how you can work with others to achieve great results!
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 don’t miss out on any important updates from our team!
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. Be ready to discuss your previous projects and how you applied these models in real-world scenarios.
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, prepare examples of how you've successfully collaborated in the past. Highlight any experiences where you worked with different departments to achieve a common goal.
✨A/B Testing is Key
Understand the principles of A/B testing inside out. Be prepared to explain how you would design an A/B test for a recommendation system and what metrics you would use to measure success.
✨Get Comfortable with Tech Stack
Familiarise yourself with Python, PySpark, and cloud platforms. If you have experience with these technologies, be ready to discuss specific projects where you utilised them effectively.
