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KAYAK, part of Booking Holdings, is the world's leading travel search engine. The company operates a portfolio of global metasearch brands including momondo, Cheapflights, and HotelsCombined. You'll join a team focused on building the best travel search engine to make it easier for everyone to experience the world.
In this role, you will translate product and business challenges into well-defined modeling problems, hypotheses, and measurable objectives. You'll ship production-ready, scalable machine learning solutions with real-world impact on user experience and key business metrics. Your work will focus on building recommendation systems that improve how travelers discover and choose travel options.
You'll design and evaluate experiments, build rapid prototypes, assess results rigorously, and iterate on promising ideas. Collaboration is central to the role—you'll work across Data Science, Product, and Engineering teams, communicating findings, recommendations, and trade-offs clearly to both technical and non-technical audiences. This is a hybrid role requiring 3 days per week in the Zurich office.
REQUIREMENTS:
- Strong technical foundations in statistics, machine learning, and programming, with a demonstrated track record of solving complex, real-world data science problems. Demonstrated capability matters more than academic credentials.
- Hands-on experience developing ML models in business or production environments, with the ability to clearly explain the problems addressed, your specific contributions, and the resulting impact.
- Ownership, sound judgment, and analytical thinking, with the ability to navigate technical trade-offs, work independently, and recognize when to seek guidance.
- Fluency with AI-assisted workflows, leveraging modern tools to improve productivity and quality while critically evaluating their outputs and limitations.
- Curiosity, humility, and a collaborative mindset, with a commitment to continuous learning, sharing knowledge, and improving together.
BONUS QUALIFICATIONS:
- Hands-on experience with PyTorch, Polars, CometML, Arize, Docker, Airflow, Trino, and Git/Github.
- Familiarity with Agile ways of working, such as sprint planning and team ceremonies.
