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Day 22
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Zurich Office · Zurich, Switzerland
Live, first seen by us 22 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Cost Centers › Technology › DataFrom the employer’s posting
Turn product and business challenges into measurable modeling problems
Ship production-ready, scalable machine learning solutions
Design experiments, build prototypes, and assess results rigorously
Explain findings and trade-offs to technical and non-technical audiences
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.
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
Hands-on experience developing ML models in business or production environments
backed by a track record of solving complex, real-world data science problems
Fluency with AI-assisted workflows
From the employer’s posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 22
Similar jobs usually come down between day 7 and day 55.
From 10,040 similar postings that came down. Coming down is not always a hire.
10 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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.
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Yes. We’ve followed one other Data Scientist job there since October 2026. It is still up.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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 Zurich office 3 days per week.
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.
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-learnings
Travel Discounts
Employee Resource Groups
5 weeks paid vacation + a day off for your birthday
Social events & Thursday happy hours
Free lunch 2 days per week
Pension plan contributions
Supplemental accident insurance
Health insurance subsidy of 250 CHF per month
Lunch Check Card of 180 CHF per month
Profawo membership which is a non-profit organization dedicated to promoting the compatibility of family and work
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.
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Zurich, Switzerland
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