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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Scientist II - **Company:** Booking.com - **Location:** Amsterdam, Netherlands - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Big Data, BigQuery, Code Reuse, Data Visualization, Python (Programming Language), Machine Learning, Open Source Technology, Rapid Prototyping Process, Software Deployment, Software Engineering, SQL Databases, Google Cloud, Apache Spark, Information Technology, Data Analytics, Machine Learning Operations, Data Generation - **Published:** September 25, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2c69a9c783d9bdd6 ## About the Role 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., * 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. ## Description * 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Introduction to sCrypt - a smart contract language for Bitcoin SV](https://www.wearedevelopers.com/videos/24-introduction-to-scrypt-a-smart-contract-language-for-bitcoin-sv) - [Making Data Warehouses fast. 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