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Machine Learning Scientist

Booking.com

Amsterdam, North Holland, Netherlands
Full-time
Salary not listedPosted 6m ago

Real job — pulled straight from Booking.com’s careers page · Verified September 24, 2026 · No reposts.

Job description

Booking.com is hiring a Machine Learning Scientist — a full-time, based in Amsterdam, North Holland, Netherlands role. Apply directly on Booking.com's careers page below.

Machine Learning Scientist II

Location: Amsterdam, North Holland, Netherlands

 

About Us: At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world.

About the team: The Performance Marketing team builds and optimizes large‑scale ML systems for online bidding across all major search providers, owning one of the industry’s largest online advertising optimization platforms to keep Booking.com competitive. We run end‑to‑end research‑to‑production cycles—from POC models to production A/B tests—driving measurable impact by innovating in online auctions at scale.

Role Description: As a Machine Learning Scientist, you’ll have the chance to work on diverse marketing surfaces and play an integral role in taking our bidding algorithms to the next level across verticals. You’ll have the chance to collaborate closely with other machine learning scientists,, engineers, and various business stakeholders and take full ownership of your work - from the initial idea generation phase to the implementation of the final Machine Learning product. You will thrive at Booking.com if you are result-focused, innovative, and with a solid quantitative background, but most of all by understanding our complex business problems and the customer-centric approach we apply to solve these problems.

 Key Job Responsibilities and Duties:

  • Devise and develop state-of-the-art techniques for the next phase of our online bidding algorithms, including user-intent modeling, online marketplace modeling, and bidding strategy optimization to maximize the efficiency of our advertising spend.

  • Design and implement scalable evaluation pipelines and frameworks, including simulations, synthetic data generation, benchmarking, and offline and online evaluation for model quality, relevance, and consistency.

  • Ensure the reliability, efficiency, and scalability of evaluation tools and frameworks, and translate quality-related ideas into actionable platform capabilities and safeguards.

  • Conduct in-depth data analysis to define and track evaluation metrics, validate label quality, and explore performance across different traffic segments.

  • Identify opportunities to improve our machine learning systems development processes, and drive improvements in how we build, evaluate, and ship ML systems.

  • Build readable and reusable code, choosing the right technologies, methodologies, and engineering approach from rapid prototyping to production deployment at scale.

  • Improve, scale, and extend machine learning tooling and infrastructure, in collaboration with business-specific teams and ML engineers.

  • 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, while maintaining a cross-disciplinary perspective across ML/AI methods and related fields.

Role Qualifications and Requirements:

  • Master’s degree or PhD required (Computer Science, Engineering, Mathematics, Artificial Intelligence, Physics, Economics, Econometrics)

  • 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/or 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, GCP, 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 

  • 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

 

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. 

 

Take it from our Chief People Officer, Paulo Pisano: “At Booking.com, the diversity of our people doesn’t just build an outstanding workplace, it also creates a better and more inclusive travel experience for everyone. Inclusion is at the heart of everything we do. It’s a place where you can make your mark and have a real impact in travel and tech.” 

 

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: 

  • Let’s go places together: How we Hire

  • 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. We strive to move well beyond traditional equal opportunity and work to create an environment that allows everyone to thrive.


Key Skills

ML


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.

Qualifications

ML

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Frequently asked questions

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You can view the full description and apply for Machine Learning Scientist at Booking.com on EchoJobs: https://echojobs.io/job/booking-com-machine-learning-scientist-ii-5iob8.