Machine Learning Scientist II

ppbAbout Us: /b 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. /p pbAbout the team: /b 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. /p pbRole Description: /b 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. /p pbKey Job Responsibilities and Duties: /b /p ul liDevise 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. /li liDesign and implement scalable evaluation pipelines and frameworks, including simulations, synthetic data generation, benchmarking, and offline and online evaluation for model quality, relevance, and consistency. /li liEnsure the reliability, efficiency, and scalability of evaluation tools and frameworks, and translate quality‑related ideas into actionable platform capabilities and safeguards. /li liConduct in‑depth data analysis to define and track evaluation metrics, validate label quality, and explore performance across different traffic segments. /li liIdentify opportunities to improve our machine learning systems development processes, and drive improvements in how we build, evaluate, and ship ML systems. /li liBuild readable and reusable code, choosing the right technologies, methodologies, and engineering approach from rapid prototyping to production deployment at scale. /li liImprove, scale, and extend machine learning tooling and infrastructure, in collaboration with business‑specific teams and ML engineers. /li liCollaborate closely with ML engineers to integrate evaluation components into production pipelines, supporting continuous improvement of bidding applications. /li liWork 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. /li /ul h3bRole Qualifications and Requirements: /b /h3 ul liMaster’s degree or PhD required (Computer Science, Engineering, Mathematics, Artificial Intelligence, Physics, Economics, Econometrics) /li liIndustry or academia knowledge of large scale optimisation techniques or mechanism design or auction theory. /li liProven 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. /li liRelevant 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. /li liExperience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development. /li liExperience collaborating cross functionally in the development of machine learning products (e.g. Developers, Commercial, Data Analytics, etc.). /li liVery strong working knowledge of Python, GCP, SQL/BigQuery, Spark /li liExcellent English communication skills, both written and verbal. /li /ul pbBenefits Perks - Global Impact, Personal Relevance: /b /p pBooking.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: /p ul liAnnual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave /li liHybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country) /li liIndustry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit /li liLiving and working in Amsterdam, one of the most cosmopolitan cities in Europe /li liContributing to a high scale, complex, world renowned product and seeing real‑time impact of your work on millions of travelers worldwide /li liWorking in a fast‑paced and performance driven culture /li liOpportunity to utilize technical expertise, leadership capabilities and entrepreneurial spirit /li liPromote and drive impactful and innovative engineering solutions /li liTechnical, behavioral and interpersonal competence advancement via on‑the‑job opportunities, experimental projects, hackathons, conferences and active community participation /li liCompetitive compensation and benefits package and some great added perks of working in the home city of Booking.com /li /ul pbDiversity, Equity and Inclusion (DEI) at Booking.com: /b /p pDiversity, 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. /p pTake 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.” /p pWe 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. /p pBooking.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. /p pbPre-Employment Screening: /b /p pIf 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. /p pbKey Skills /b /p pML /p /p #J-18808-Ljbffr