Data Scientist II, HMS - 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.

Horizontal Marketing Services (HMS) is looking for an experienced Data Scientist II to help develop accurate and meaningful statistical models to measure the short and long term impact of various campaigns across different marketing channels and drive incremental performance.

In this role, you will be responsible for high-impact projects aimed at measuring marketing effectiveness and optimizing the performance of our marketing spend. Projects may include (but not limited to) using econometric models to measure the ROI of online and offline Brand activities, design and analysis of non-randomized experiments, and measuring the incrementality of marketing spend, various marketing campaigns, and product / service offerings. The output of your work will be used to help inform the marketing strategy for the future of Booking.com. You will also work proactively with many stakeholders across different teams to set up measurement frameworks for various marketing activities to determine the success.

We want someone with a proven ability to use statistics, econometric and ML models to uncover complex relationships in data and use these insights to achieve business goals. The successful candidate should have a background such as in econometrics, statistics, mathematics, data science, computer science, and have experience using sophisticated statistical methods in an applied business setting.

Key Responsibilities

1. 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.
2. 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.
3. 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.
4. Responsible for designing and interpreting quantitative experiments to objectively guide key business decision making.
5. 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.
6. 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 their peer's when a more efficient way presents itself.
7. Responsible for leveraging Data Science for impact while learning to incorporate scalability, reproducibility and long term orientation in their work.
8. 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.
9. 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.
10. ​​Must be knowledgeable about the larger data ecosystem at Booking and how it relates to the work they do.
11. Responsible for collaborating with peers in related crafts (ie. Data Engineering), anticipating data needs to ensure smooth progress of their individual projects.
12. 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).
13. Responsible for ensuring quality of their own work by validating it through peer review.
14. Responsible for influencing business decisions within their specific area (ie. product team).

• Strong knowledge and experience in causal inference with observational data, econometric and ML models, marketing attribution, and incrementality modeling
• Experience in experimentation: A/B testing, geo-testing, power analysis, sample size determination, minimum detectable effect sizes, familiarity with biases in experimentation, meta-analysis etc.
• Strong working knowledge of descriptive and inferential statistics.
• Experience solving real problems using data mining techniques and with statistical rigor
• Excellent communication skills
• Strong skills in translating business problems into data problems
• Strong stakeholder management
• Strong coding and data visualization skills
• Strong skills in storytelling with data
• Strong knowledge of data management (engineering, data pipelines, workflows)
• Strong knowledge of the possibilities and limitations of different types of data analysis and/or data science modeling

• Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave
• Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country)
• Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and Booking.com wallet credit