At a Glance
- Tasks: Develop and optimise cutting-edge ML algorithms for performance marketing.
- Company: Join Booking.com, a leader in travel tech with a vibrant culture.
- Benefits: Enjoy competitive pay, flexible work, and unique travel perks.
- Why this job: Make a real impact on millions of travellers while innovating in tech.
- Qualifications: Master’s or PhD in relevant fields; experience in ML and optimisation required.
- Other info: Diverse and inclusive workplace with excellent growth opportunities.
The predicted salary is between 36000 - 60000 ÂŁ per year.
About Us
At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. Through our products, partners and people, we make it easier for everyone to experience the world.
About the team
The PPC team builds and optimizes large‑scale ML models for online bidding across all major search providers, owning one of the industry’s largest performance and auction strategies to keep Booking.com competitive. We run end‑to‑end research‑to‑production cycles—from POCs and modeling to large‑scale A/B testing—driving measurable impact by optimizing auction levers at scale.
Role description
As a Machine Learning Scientist in PPC, your work will focus on devising and implementing advanced machine learning and optimization approaches for the next generation of Booking.com performance marketing bidding algorithms. Specifically, you will work on optimizing our bidding strategy across search platforms, ensuring our competitive edge in the complex dynamics of the bidding marketplace and online auction mechanisms. This role requires a unique combination of deep theoretical knowledge around large‑scale optimization techniques, auction theory and applying state of the art machine learning methodologies to scalable industrial setups.
Key Job Responsibilities and Duties
- Develop innovative techniques for the next phase of our online bidding algorithms, including modeling user intent, modeling the online marketplaces, and optimizing our bidding strategy to maximize the efficiency of how we spend our advertising budgets.
- Design and implement scalable evaluation pipelines, including synthetic data generation and benchmarking for model quality, relevance, and consistency.
- Ensure the reliability, efficiency, and scalability of evaluation tools and frameworks in both offline and online environments.
- Conduct in‑depth data analysis to define and track evaluation metrics, validate label quality, and explore performance across different traffic siloes.
- Collaborate closely with ML engineers to integrate evaluation components into production pipelines, supporting continuous improvement of bidding applications.
- Work cross‑functionally with commercial and analytics teams to align evaluation strategies with business goals and user impact.
Role qualifications and requirements
- Master’s degree or PhD required (Computer Science, Engineering, Mathematics, Artificial Intelligence, Physics).
- Industry or academia knowledge of large scale optimisation techniques or mechanism design or auction theory.
- Experience contributing to innovative machine learning and optimization solutions for large‑scale business problems.
- Preferably evidenced by peer‑reviewed publication, patents, open sourced code or the like.
- Relevant work or academic experience (MSc + 1 year of working experience), involved in the application of Machine Learning to business problems.
- Knowledge of some machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
- Understanding of cross‑functional development of machine learning products (e.g. Developers, Commercial, Data Analytics, etc.).
- Working knowledge of Python, SQL/BigQuery, Spark.
- Excellent English communication skills, both written and verbal.
Benefits & Perks - Global Impact, Personal Relevance
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive compensation and benefits package, as well unique‑to‑Booking.com benefits which include:
- Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave.
- Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country).
- Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit.
- Contributing to a high scale, complex, world renowned product and seeing real‑time impact of your work on millions of travelers worldwide.
- Working in a fast‑paced and performance driven culture.
- Opportunity to utilize technical expertise, leadership capabilities and entrepreneurial spirit.
- Promote and drive impactful and innovative engineering solutions.
- Technical, behavioral and interpersonal competence advancement via on‑the‑job opportunities, experimental projects, hackathons, conferences and active community participation.
Diversity, Equity and Inclusion (DEI) at Booking.com
Diversity, Equity & Inclusion have been a core part of our company culture since day one. This ongoing journey starts with our very own employees, who represent over 140 nationalities and a wide range of ethnic and social backgrounds, genders and sexual orientations.
We ensure that colleagues with disabilities are provided the adjustments and tools they need to participate in the job application and interview process, to perform crucial job functions, and to receive other benefits and privileges of employment.
Application Process
This role does not come with relocation assistance. Booking.com is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Machine Learning Scientist I - Performance Marketing in Manchester employer: Booking Holdings, Inc.
Contact Detail:
Booking Holdings, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Scientist I - Performance Marketing in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Booking.com. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Prepare for interviews by brushing up on your machine learning knowledge and optimisation techniques. Be ready to discuss your past projects and how they relate to performance marketing.
✨Tip Number 3
Showcase your passion for travel and tech during interviews. Booking.com thrives on innovation, so let your enthusiasm shine through!
✨Tip Number 4
Apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Machine Learning Scientist I - Performance Marketing in Manchester
Some tips for your application 🫡
Show Your Passion for Data: When you're writing your application, let your enthusiasm for data and technology shine through. We want to see how you connect with the thrill of using data to drive decisions and create memorable experiences.
Highlight Relevant Experience: Make sure to showcase any experience you have with machine learning, optimisation techniques, or auction theory. We love seeing how you've tackled large-scale business problems in the past, so don't hold back!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to explain your skills and experiences. We appreciate a well-structured application that makes it easy for us to see why you're a great fit.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at Booking.com.
How to prepare for a job interview at Booking Holdings, Inc.
✨Know Your Algorithms
Make sure you brush up on your machine learning algorithms and optimisation techniques. Be ready to discuss how you've applied these in real-world scenarios, especially in relation to bidding strategies or auction theory.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, particularly those involving large-scale data sets or innovative ML solutions. If you have publications or open-source contributions, bring them up to demonstrate your expertise.
✨Understand the Business Impact
Familiarise yourself with how machine learning impacts performance marketing. Be prepared to discuss how your work can drive measurable results and align with business goals, as this is crucial for the role.
✨Practice Collaboration Scenarios
Since you'll be working cross-functionally, think of examples where you've successfully collaborated with other teams. Highlight your communication skills and how you’ve integrated feedback from different stakeholders into your projects.