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- Tasks: Design and implement machine learning models to optimise bidding strategies and investment allocation.
- Company: Join Expedia Group, a leader in global travel technology.
- Benefits: Enjoy travel perks, generous time-off, flexible work, and career development resources.
- Why this job: Shape the future of travel with cutting-edge tech and impactful solutions.
- Qualifications: Bachelor's or Master's in a quantitative field and 2+ years of machine learning experience.
- Other info: Be part of a diverse community that celebrates differences and fosters growth.
The predicted salary is between 36000 - 60000 £ per year.
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 team:
The Search Product & Optimization team at Expedia Group sits within the Marketing division and is responsible for the algorithmic intelligence behind our global marketing investments. We operate in a fast-paced and dynamic environment, participating in millions of auctions daily across Search, Metasearch and Social platforms. Our mission is to build scalable, data-driven systems that optimize how we acquire traffic. We are moving beyond traditional analytics to develop automated decisioning systems that dynamically allocate investment to maximize business value. We operate under a build & scale philosophy, creating solutions that adapt to a rapidly evolving search marketing landscape.
In this role, you will:
- Design and implement machine learning models to optimize bidding strategies (e.g., Cost-Per-Click, Target ROAS, Target CPA) and investment allocation across diverse marketing channels.
- Develop methodologies to measure elasticity (how performance changes as spend scales) to help us answer granular capital allocation questions.
- Write clean, efficient and reproducible Python code. You will partner with Machine Learning Engineers to deploy your models into production environments, ensuring they are robust and scalable.
- Contribute to the development of feedback loops and control mechanisms that allow our bidding systems to self-correct and adapt to market volatility or competitor changes.
- Design and analyze A/B experiments to validate model performance and inform strategic decisions.
- Translate mathematical concepts into clear insights for business partners. You will help frame vague business problems into concrete analytical tasks and define the objective functions that our models solve for.
Experience & Qualifications:
- Bachelor or Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics, etc.) or equivalent practical experience.
- 2+ years of professional experience applying Machine Learning to real-world business problems.
- Strong Python proficiency in writing production-quality code and using libraries like pandas, scikit-learn, numpy.
- Advanced SQL ability to write complex queries to handle large-scale datasets.
- Solid understanding of regression (GLMs), optimization techniques, time-series forecasting and probability theory.
- A strong interest in AdTech, Bidding Markets, Game Theory, or Control Systems. You are curious about how auctions work and how to optimize within them.
- Comfortable working with ambiguity. You can take a high-level goal and break it down into a solvable mathematical problem.
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 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, Search Marketing Bidding in London employer: Expedia, Inc.
Contact Detail:
Expedia, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Scientist II, Search Marketing Bidding in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Expedia Group. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your machine learning expertise. When you get the chance to chat with recruiters, having something tangible to discuss can really set you apart.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your Python coding skills and understanding key concepts in machine learning. Mock interviews can help you feel more confident when it’s time to shine.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, you’ll be part of a community that values diversity and innovation, which is exactly what we’re all about at Expedia Group.
We think you need these skills to ace Machine Learning Scientist II, Search Marketing Bidding in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Machine Learning Scientist II role. Highlight your experience with machine learning models and how they relate to bidding strategies, as this will show us you understand what we're looking for.
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of projects where you've used Python, SQL, or any relevant machine learning techniques. We want to see how you’ve applied your knowledge in real-world scenarios.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's necessary. We appreciate a well-structured application that gets straight to the point while still showcasing your personality.
Apply Through Our Website: We encourage you to apply directly through our website. This way, your application will be processed more efficiently, and you'll have access to all the latest updates about the role and our company culture!
How to prepare for a job interview at Expedia, Inc.
✨Know Your Algorithms
Make sure you brush up on your machine learning algorithms, especially those related to bidding strategies like Cost-Per-Click and Target ROAS. Be ready to discuss how you've applied these in real-world scenarios, as this will show your practical experience.
✨Showcase Your Coding Skills
Since strong Python proficiency is key for this role, prepare to demonstrate your coding skills. You might be asked to write some production-quality code on the spot, so practice writing clean and efficient scripts using libraries like pandas and scikit-learn.
✨Understand the Business Impact
Be prepared to translate complex mathematical concepts into business insights. Think about how your work can drive real-world actions and financial returns, and be ready to discuss specific examples of how you've done this in the past.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to handle ambiguity and break down high-level goals into solvable problems. Practice articulating your thought process clearly, as this will demonstrate your analytical skills and strategic thinking.
