At a Glance
- Tasks: Build cutting-edge ML solutions for personalised recommendations and relevance optimisation.
- Company: Join the innovative Expedia Group B2B Machine Learning Science team.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and tackle exciting challenges.
- Why this job: Make a real impact with your skills in a dynamic tech environment.
- Qualifications: Ph.D. or master's in relevant fields; Python proficiency required.
The predicted salary is between 55000 - 70000 £ per year.
We are looking for a Machine Learning Scientist II to join the Expedia Group B2B Machine Learning Science team. In this role, you will build end‑to‑end ML solutions for personalized recommendations, learning to rank, and relevance optimization, driving substantial value for our partners and Expedia Group.
Responsibilities
- Develop and implement ML models for recommendations and relevance at scale that can handle high-throughput, low-latency personalized recommendations across diverse partner segments.
- 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 deploy models across the tech stack.
Qualifications
- Ph.D. (preferred) or master’s degree in computer science, machine learning, mathematics/statistics, or another related field.
- 2 years of industry experience in applying ML to real‑world problems (desirable but not required).
- Proficiency in Python, with experience using PySpark and common machine learning libraries and frameworks such as scikit‑learn, TensorFlow, and Keras.
- Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud computing platforms (AWS, GCP).
- Solid understanding of common machine learning algorithms.
- Knowledge of statistics and probability theory.
- Excellent problem‑solving skills and ability to learn new concepts quickly.
- Strong communication skills and ability to explain complex technical concepts to non‑technical stakeholders.
- Enthusiasm for tackling challenging problems and contributing to innovative solutions.
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.
Equal Employment Opportunity
Expedia Group 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.
Machine Learning Scientist II in London employer: 11310 Expedia.com Ltd.
Expedia Group is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Machine Learning Scientist II role. With a commitment to employee growth, you will have access to cutting-edge technologies and the opportunity to work on impactful projects that drive value for partners. Located in a dynamic environment, Expedia Group prioritises inclusivity and offers a supportive atmosphere where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Scientist II in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, experiments, and any A/B tests you've run. This will give potential employers a taste of what you can do and how you think.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Machine Learning Scientist II in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning and relevant technologies. 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 tell us why you’re the perfect fit for the Machine Learning Scientist II position. Share your passion for ML and how you can contribute to our team’s success. Keep it engaging and personal!
Showcase Your Technical Skills:We love seeing practical examples of your work! Include links to any GitHub repositories or projects that demonstrate your proficiency in Python, PySpark, and ML frameworks. This helps us understand your hands-on experience.
Be Clear and Concise:When writing your application, clarity is key. Use straightforward language to explain your methodologies and results. Remember, we want to see how well you can communicate complex ideas to both technical and non-technical audiences!
How to prepare for a job interview at 11310 Expedia.com Ltd.
✨Know Your ML Models Inside Out
Make sure you’re well-versed in the machine learning models relevant to the role. Be prepared to discuss your experience with recommendations, learning to rank, and relevance optimisation. Brush up on the algorithms you’ve used and be ready to explain how they work and their applications.
✨Showcase Your Problem-Solving Skills
During the interview, highlight specific examples where you've tackled complex problems using ML. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will demonstrate your analytical thinking and ability to apply your knowledge to real-world scenarios.
✨Communicate Clearly with Non-Technical Audiences
Since you'll need to explain technical concepts to non-technical stakeholders, practice simplifying your explanations. Think of ways to convey your methodologies and results in layman's terms. This skill is crucial for collaboration across teams and will set you apart.
✨Stay Updated on ML Trends
Research the latest trends and advancements in machine learning before your interview. Being able to discuss recent developments or techniques shows your enthusiasm for the field and your commitment to continuous learning, which is highly valued in this role.
