Kayak
Data Scientist
Zurich Office, Remote. Posted a month ago
The role
A mid-level Data Scientist will build recommendation systems to improve how travelers discover and choose travel options. You will translate business questions into modeling problems and partner with cross-functional teams to bring solutions into production.
What you will do
- Translate product and business challenges into well-defined modeling problems, hypotheses, and measurable objectives.
- Ship production-ready, scalable Machine Learning solutions.
- Design and evaluate experiments, building rapid prototypes and assessing results.
- Collaborate across Data Science, Product, and Engineering.
- Communicate findings, recommendations, and trade-offs to technical and non-technical audiences.
Required qualifications
- Strong technical foundations in statistics, machine learning, and programming.
- Track record of solving complex, real-world data science problems.
- Hands-on experience developing ML models in business or production environments.
- Ability to explain problems addressed, specific contributions, and resulting impact.
- Ownership, sound judgment, and analytical thinking.
- Ability to navigate technical trade-offs and work independently.
- Fluency with AI-assisted workflows.
Nice to have
- 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.
Benefits
- Work from (almost) anywhere for up to 20 days per year
- Company-paid therapy sessions through SpringHealth
- Company-paid subscription to HeadSpace
- Company-wide week off a year
- No meeting Fridays
- Paid parental leave
- Paid volunteer time
- Development Dollars
- Leadership development
- Access to thousands of on-demand e-learnings
- Travel Discounts
- Employee Resource Groups
About the company
KAYAK is a travel search engine and part of Booking Holdings. It operates a portfolio of global metasearch brands including momondo, Cheapflights and HotelsCombined.