Data Scientist at KAYAK

berlin, Berlin, Germany -

Full Time

Start Date

Immediate

Expiry Date

15 Jan, 27

Salary

65000.0

Posted On

17 Oct, 26

Experience

4 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Industry

Information Technology & Services

Description

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.
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 technologies relevant to KAYAK’s stack, such as PyTorch, Polars, CometML, Arize, Docker, Airflow, Trino and Git/Github.
Familiarity with Agile ways of working, such as sprint planning and team ceremonies.

Responsibilities