Data Scientist

KAYAK, part of Booking Holdings (NASDAQ: BKNG), is the world's leading travel search engine. With billions of queries across our platforms, we help people find their perfect flight, stay, rental car and vacation package. We're also transforming business travel with a new corporate travel solution, KAYAK for Business.

As an employee of KAYAK, you will be part of a travel company that operates a portfolio of global metasearch brands including momondo, Cheapflights and HotelsCombined, among others. From start-up to industry leader, innovation is at our core and every employee has an opportunity to make their mark. Our focus is on building the best travel search engine to make it easier for everyone to experience the world.

KAYAK is looking for a mid-level Data Scientist to build recommendation systems that improve how travelers discover and choose travel options.

You’ll translate product and business questions into measurable modeling problems, develop and test solutions with data and experimentation, and partner with researchers, engineers, and cross-functional teams to bring promising work into production. Your work will improve the traveler experience and key business metrics across KAYAK.

If you’re excited to solve challenging recommendation problems and make a measurable difference for travelers, we’d love to hear from you.

This role will be required to work from our Berlin office 3 days per week.

In this role, you will:

• Translate product and business challenges into well-defined modeling problems, hypotheses, and measurable objectives.

• Ship production-ready, scalable Machine Learning solutions with real-world impact on user experience and key business metrics.

• Design and evaluate experiments, building rapid prototypes, assessing results rigorously, and iterating on promising ideas.

• Collaborate across Data Science, Product, and Engineering, communicating findings, recommendations, and trade-offs clearly and concisely to both technical and non-technical audiences.

Please apply if you have:

• Strong technical foundations in statistics, machine learning, and programming, backed by a 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.