Data Scientist

Software Engineer @ KAYAK Software Corporation; Berlin; Hybrid; EUR 70,000 - 90,000; Full time

Benefits offered by this job

Work from almost anywhere up to 20% of

Mental health focus

No meeting Fridays

Paid parental leave

Paid volunteer time

Development dollars

Leadership development

On-demand e-learning

Travel discounts

Office in Berlin

Job summary

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 collaborate with researchers, engineers, and cross-functional teams to bring promising work into production.

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

Qualifications

• Strong foundations in statistics, machine learning, and programming.
• Experience building ML models in production with measurable impact.
• Ability to communicate findings to technical and non-technical audiences.

Responsibilities

• Translate product and business challenges into well-defined modeling problems, hypotheses, and measurable objectives.
• Ship production-ready, scalable ML 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.

Skills

Statistics

Machine Learning

Programming

Experimentation

Communication

Collaboration

Independent thinking

AI workflows

Tools

PyTorch

Polars

CometML

Arize

Docker

Airflow

Trino

Git/Github

Job description

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.

• 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.

Benefits and Perks:

• Work from (almost) anywhere for up to 20 days per year
• Focus on mental health and well-being:
  • Company-paid therapy sessions through SpringHealth
  • Company-paid subscription to HeadSpace
  • Company‑wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
• No meeting Fridays
• Paid parental leave
• Paid volunteer time
• Focus on your career growth:
  • Development Dollars
  • Leadership development
  • Access to thousands of on-demand e‑learning(s?)
• Travel Discounts
• Employee Resource Groups
• 6 weeks paid vacation + a day off for your birthday
• Free lunch 2 days per week
• Pension plan contributions
• Public transportation subsidies
• Bike leasing program
• Monthly social events, Thursday happy hours, sports teams
• An awesome office in Friedrichshain, Berlin

Inclusion

At KAYAK, we want everyone to have the space to grow, share ideas and do great work. That's why we're focused on hiring the best talent from all walks of life and experiences, supporting them well and making sure no one feels like they have to fit a mold to belong here.

Need any adjustments for the interview, application or on the job? No problem - just give us a heads‑up. We've got you.