Data Scientist- Performance Marketing

About Us

At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world.

About our team

The PPC team builds and optimizes large-scale ML models for online bidding across all major search providers, owning one of the industry’s largest performance and auction strategies to keep Booking.com competitive. We run end-to-end research-to-production cycles—from POCs and modeling to large-scale A/B testing—driving measurable impact by optimizing auction levers at scale.

Role Overview

Data Scientists take full ownership of the design and delivery of data science solutions, from ideation to implementation. They work independently on tasks like data consumption, preparation, and the translation of business problems into data stories. This role involves applying suitable statistical data analysis and modeling methods to solve complex business problems.

Data Scientist works within the scope of their team, and occasionally across partner teams, to inform business decisions. They independently identify and manage stakeholders, effectively communicating complex analysis results. As experienced members of the team, they provide guidance to junior colleagues, act as force multipliers, and contribute significantly to their community. They stay updated about the larger data ecosystem and the goals of their track and business unit, ensuring the quality of their work through peer review. They play a key role in influencing business decisions within their specific area.

Key Job Responsibilities and Duties

• Responsible for owning the design and delivery of entire Data Science solutions based on business requirements, bringing them from the initial idea-generation phase to implementation independently.
• Responsible for working autonomously on consuming data, preparing it for data science use, translating business problems to data stories and solving them effectively by applying suitable statistical data analysis and modeling methods. Leverages input from business stakeholders in all of the above to determine the right technical solutions to deliver customer value.
• Responsible for working primarily within the scope of their team to deliver work that informs business decisions for the product / business topic they currently work on, occasionally collaborating across multiple teams.
• Responsible for designing and interpreting quantitative experiments to objectively guide key business decision making.
• Responsible for independently identifying and managing stakeholders in operational, project-based, and managerial roles. Effectively communicates, addresses stakeholder needs, and conveys complex analysis results in a clear manner. Begins to guide junior colleagues in stakeholder engagement.
• Responsible for being flexible in adopting existing internal and external Data Science approaches, proposing and spotting opportunities to apply new approaches and expanding their technical competencies and that of their peers when a more efficient way presents itself.
• Responsible for leveraging Data Science for impact while learning to incorporate scalability, reproducibility and long term orientation in their work.
• Responsible for acting as a force multiplier for junior peers in the team by actively helping them with their craft through means of coaching, mentoring and setting a good example.
• Responsible for contributing to the community of their area by supporting community projects aimed at making other data professional more effective, actively participating in community strengthening activities (ie. recruitment) and connecting with peers beyond their area.
• Must be knowledgeable about the larger data ecosystem at Booking and how it relates to the work they do.
• Responsible for collaborating with peers in related crafts (ie. Data Engineering), anticipating data needs to ensure smooth progress of their individual projects.
• Must be knowledgeable with the operational, tactical and strategic goals of their area (ie. track / vertical) and have high level knowledge of the goals of their wider area (ie. Business Unit).
• Responsible for ensuring quality of their own work by validating it through peer review.
• Responsible for influencing business decisions within their specific area.