Data Scientist II - Finance

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.

Job Summary:

Order to Cash is looking for an experienced Data Scientist II to help design and run data science solutions to measure and optimize our O2C operations efforts across different pillars from collections, payouts and revenue operations.

In this role, you are expected to take full ownership of the design and delivery of data science solutions, from ideation to implementation. You will 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 II works within the scope of their team, and occasionally across partner teams, to inform business decisions. You will be working independently to identify and manage stakeholders, effectively communicating complex analysis results. As an experienced member of the O2C Global Finance Analytics team, you are expected to provide guidance to junior colleagues, act as force multipliers, and contribute significantly to their community. The role should 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. You will play a key role in influencing business decisions within O2C and across departments.

• 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 their peer's 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 (ie. product team).

• Experience solving real problems using data mining techniques and with statistical rigor and translating business problems into data problems
• Knowledge and practical experience of Statistical Methods (e.g. Testing, GLM, Inference), Statistical/Machine Learning (e.g. Dimension Reduction, Clustering, Regularisation, Bagged/Boosted methods), Time Series, etc
• Strong experience of A/B Testing and a range of Experimentation methods
• Strong experience in data engineering concepts: ETL, data warehousing, data modeling, and data quality management
• Solid understanding of DBT, Snowflake, Spark, SQL, Python and/or R
• Solid understanding of data management (schema design, data pipelines, workflows)
• Strong stakeholder management
• Strong data visualization skills
• Strong skills in storytelling with data
• Proven understanding of the possibilities and limitations of different types of data analysis and/or data science modelling

• 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

• Let's go places together: How we Hire
• Detailed instructions on post-application requirements including any required application materials, deadlines, portfolios, coding challenges, or other assessments as defined by BU or department.