Data Scientist - Price at trivago
May no longer be active — verify on the employer site
At a glance
- Company
- trivago
- Location
- Düsseldorf, Germany
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this trivago job
- 🏢 trivago has 12 jobs here, 12 with visa sponsorship see all
- 🛂 Visa: EU Blue Card. Minimum salary: €50,700 a year guide
- 💡 No salary shown. Ask trivago if it is above the minimum.
Updated 2026-11-05, from our data and official sources.
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About the role
Responsibilities:
- Design analytical frameworks and ML models that guide pricing strategy, price prediction and caching optimization for millions of users.
- Build, deploy and maintain production-ready machine learning systems with monitoring, iteration and performance safeguards.
- Establish and run experiments (A/B tests), define evaluation metrics, and develop simulations to quantify impact.
- Translate complex business problems into technical solutions through close collaboration with product managers and engineers.
- Communicate findings and strategic recommendations clearly to stakeholders using concise data storytelling.
- Mentor and review work of junior data scientists to raise team quality and disseminate best practices.
Requirements:
- 5+ years of industry experience delivering impactful analyses and production ML models in data science or applied science roles.
- Advanced degree (MSc or PhD) in computer science, statistics, engineering, mathematics, economics, or a related quantitative field.
- Proven experience deploying and operating ML models in production, including monitoring and iterative improvement.
- Strong foundation in experimental design, statistical testing, time-series analysis and optimization methods.
- Proficiency with Python or R, SQL, and familiarity with cloud platforms and big-data tooling (e.g., GCP).
- Experience with real-time systems, caching strategies, dynamic pricing, or reinforcement learning/bandit methods is a plus.
- Excellent collaboration and communication skills to influence product and engineering teams.
Responsibilities
Design and optimize ML models and analytical frameworks to revolutionize hotel price discovery and caching for millions of users. Collaborate cross-functionally to translate business problems into technical solutions and mentor junior data scientists.
Requirements
Requires 5+ years of industry experience in data science and an advanced degree in a quantitative field. Must have proven expertise in deploying production ML models, statistical testing, and proficiency in Python/R and SQL.
Key skills
- Machine Learning — in 291 other listings on The Stack
- Python — in 1200 other listings on The Stack
- R — in 45 other listings on The Stack
- SQL — in 545 other listings on The Stack
- GCP — in 169 other listings on The Stack
- A/B Testing — in 124 other listings on The Stack
- Experimental Design — in 22 other listings on The Stack
- Time Series Analysis — in 4 other listings on The Stack
- Optimization Algorithms
- Price Prediction
- Data Storytelling
- Statistical Testing
- Big Data Technologies
- Dynamic Pricing
- Reinforcement Learning
- Production ML Deployment
On The Stack (as of 2026-11-05)
Frequently asked questions about trivago
Is this Data Scientist - Price role still open?
It was posted on 2026-06-02. Listings more than 30 days old may no longer be active, so check trivago's site before applying.
Does trivago offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on trivago's site.
Where is this role located?
The listing gives the location as Düsseldorf, Germany. It is marked on-site.
What skills does this role ask for?
The listing names: Machine Learning, Python, R, SQL, GCP, A/B Testing, Experimental Design, Time Series Analysis, Optimization Algorithms, Price Prediction, Data Storytelling, Statistical Testing, Big Data Technologies, Dynamic Pricing, Reinforcement Learning, Production ML Deployment.