As a Machine Learning Scientist in Performance Marketing, 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 on top of the most prominent online travel agencies, 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
Devise and develop state-of-the-art 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.
Proven record in devising and developing 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 + 4 years of working experience, or PhD + 2 years of working experience), involved in the application of Machine Learning to business problems.
Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, Commercial, Data Analytics, etc.).
Very strong working knowledge of Python, SQL/BigQuery, Spark
Excellent English communication skills, both written and verbal.
Booking.com’s Total Rewards Philosophy is not only about compensation but also about benefits. We offer a competitive , 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
Living and working in Amsterdam, one of the most cosmopolitan cities in Europe
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
Competitive compensation and benefits package and some great added perks of working in the home city of Booking.com
Application Process:
Let’s go places together:
This role does not come with relocation assistance.
Pre-Employment Screening
If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.
