Data Scientist - Ranking

When travelers are searching for a hotel, we want the obvious choice to be trivago! Our leading metasearch engine is super fast and constantly optimized - enabling millions of travelers to compare hotel prices from hundreds of booking sites and find great deals in just a few clicks. We use cutting-edge technology, real-time auction, and machine learning techniques with petabytes of data to create an experience - time and money saved! In the lively city of Düsseldorf, we seize opportunities to learn everyday, innovate, and make an enduring mark on the travel industry. At trivago you will find those who aren’t afraid of change but rather embrace it, turning every challenge into a pathway for growth. Join trivago, work with a great team, and grow with us!

Join us in making a difference

We're looking for an analytical and enthusiastic Data Scientist to dig into petabytes of data to further develop the accommodation recommendation engine of our global hotel search platform! As a Data Scientist in the Ranking Team, you can have a direct impact on the mechanisms that govern the interaction of a million of daily users and our hundreds of booking sites in real-time. You will work in a cross-functional team with other data scientists, engineers, and product managers to design, implement, improve our ranking algorithms and evaluate their performance on live data. If you have a background in algorithm development, machine learning, or predictive analytics and enjoy finding solutions to tricky problems, apply today!

Get an inside look at data science at trivago:

How you’ll make an impact:

• Develop our ranking algorithm by integrating various input data and experimenting with customized ranking approaches.
• Design and analyze large scale A/B tests to continuously improve and iterate upon trivago's ranking algorithms.
• Apply observational causal inference and other statistical methods (e.g. Bayesian analyses) to extract pragmatic insights and guide the development of trivago’s ranking algorithms.
• Evaluate algorithm performance and identify improvement opportunities and optimization potential.
• Push to bring new ideas into production and apply state-of-the-art models while always keeping business priorities and technical feasibility in mind.
• Determine new metrics and simulation techniques to better evaluate and anticipate test performances.
• Proactively share your conclusions and explain complex topics tailored to the audience.

What you'll need to thrive:

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Statistics, Operations Research, Mathematics, Electrical Engineering, or related fields.
• Over 4 years of work and/or research experience in the machine learning field, with a strong understanding of machine learning principles and a keen interest in applying them at scale.
• Exceptional grasp of data analysis and statistics concepts, with practical experience in applying these techniques.
• Familiarity with one of the following areas: AdTech, online marketplace, ranking, recommender systems or personalization.
• Proficiency in handling large datasets to solve complex problems.
• Hands-on experience with Python and SQL with the ability to write reusable and efficient code to automate machine learning pipelines and data processes.
• Familiarity with deep learning libraries such as TensorFlow and/or PyTorch is highly desirable, along with experience in Spark and GCP.
• Good communication skills and confidence in presenting ideas and findings to stakeholders.
• You can work well independently and prioritize effectively to maximize outcomes.

Stand out with: 

• Practical experience or solid academic research in recommender systems and ranking.

Worried about missing a few requirements? Still apply, and express your motivation as you may just be the right candidate for this or other roles!

Recruiting process for this role:

• Introduction Call
• Case Study
• Technical Interview
• Interview with Stakeholders 
• Final Interview with Lead

What you can look forward to:

As you grow, so do we.

This is why at trivago, we prioritize your development, offer personalized coaching through Likeminded, and provide workshops, educational meetups, conferences, free online learning courses, and access to a fully-equipped campus library.

Moving to join us?

No problem. You can count on the visa support from our talent support team, a relocation package, interest-free newcomer loan, free language classes, regular team and company-wide events to build experiences together.

Life happens.

We offer self-determined vacation (with a minimum of 25 vacation days), flexible working hours, 2 WFH days weekly, the chance to work remotely for 20 days abroad, free access to the Heynanny platform for personalized nanny assistance, and an on-campus kids room.

Enjoy your office days.

Use your daily canteen budget to share lunch with colleagues in our canteen, help yourself to complimentary snacks and drinks in our kitchens, stay healthy with our on-site gym and sports classes, and enjoy the comfort of ergonomic desks and focused work areas.

Thank you for considering a career at trivago! Our commitment to fostering an inclusive and enriching environment for all talents is at the heart of what we do. We understand that embarking on a new job opportunity is a blend of excitement and curiosity. Should any questions arise before you apply, feel free to reach out to us at joinus@trivago.com. Join us in our mission to make a positive impact on global travel, we look forward to your application!

#LI-Hybrid