Data Scientist - Auction
Role details
Job location
Tech stack
Job description
- Develop, optimize, and put into production algorithms critical for maintaining a fair and healthy marketplace - including models for click-through-rate prediction, advertiser rate accuracy, and reserve price optimization.
- Closely collaborate with the auction backend engineering team to ensure the seamless operation of trivago's marketplace.
- You'll also work with stakeholders beyond the auction team - from price backend to frontend - to find and display the best deals for our users.
- Analyze large-scale data to generate hypotheses about new product features and uncover long-term trends in marketplace behavior.
- Create statistical models to establish causal relationships between marketplace components.
- Design experiments, and conduct and analyze A/B tests.
- Develop metrics that measure the accuracy and fairness of our ML models, balancing a great hotel search experience for users with a healthy, competitive marketplace.
Here are some topics you'll be working on:
- How can we improve ML algorithms that leverage trivago's rich data on hotel prices and deploy low-latency models to find the best deals for our users?
- What is the causal impact of our algorithmic changes on trivago's users and marketplace dynamics?
- What are the advantages and disadvantages of different auction-based allocation and payment mechanisms?
- Can we improve the statistical tools and methods we use to test novel product features?
- How can we reduce experiment runtime without sacrificing statistical power?
- How can we best measure long-term impacts of product features?, Life happens. We offer self-determined vacation (with a minimum of 25 vacation days), flexible working hours, up to 2 work from home days weekly. Additionally you can work remotely from a different location, within Germany or selected countries abroad for up to 20 days per year. You also get free access to the Heycare 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, choose from a variety of fitness options with our on-site gym, sports classes, and Urban Sports Club membership, 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!
Requirements
Do you have a Doctoral degree?, * At least 2 years of hands-on experience in an analytics-related field.
- A strong foundation in statistics and data analysis, with experience applying it in an academic or professional context.
- An appreciation for economic reasoning, with a basic understanding of auction theory
- Proficiency in at least one statistical programming language: we write production code in Python, and team members also use R for analysis tasks.
- Experience working with SQL. A strong belief that high-quality data science requires understanding the fundamentals, being meticulous, and paying attention to detail.
- Entrepreneurial passion and ambition to drive progress and innovate.
- Motivation to continuously learn - whether in data science, mathematics, software development, or business - and to share insights with a team of equally motivated colleagues.
- Excellent communication skills (verbal and written), confidence presenting ideas and findings to stakeholders at the right level of detail.
- Fluency in English (our company language).
Stand out with:
- A PhD in a quantitative field (statistics/ML, economics, quantitative social science).
- A background in machine learning, econometrics, or causal inference.
- Experience with Bayesian statistics and probabilistic programming (Stan, PyMC or NumPyro).