Data Scientist II, Search Analytics

Our Corporate Functions are made up of teams that support Expedia Group, including our Global Finance Org., Traveler and Partner Service Platform, Legal Team, Strategy and Corporate Development Team, and People & Places Org.

The Data Scientist II, Search Analytics role is an established contributor within the analytics function, applying data science principles and playbooks to solve business problems. This role regularly interacts with stakeholders up to the Senior Manager level and plays a key part in delivering insights that drive performance improvements across the Search domain.

In this role, you will:

• Extract and combine data from multiple sources to build datasets for modeling and analytics.

• Apply statistical techniques such as regression analysis, ANOVA, and probability theory to business problems.

• Design and recommend experiments (e.g., A/B tests, pre/post analysis, causal impact) to answer strategic questions.

• Build and apply common models (e.g., linear/non-linear regression, clustering) with an understanding of data requirements and assumptions.

• Create clear, inclusive visualizations that support storytelling and deepen stakeholder understanding.

• Collaborate with stakeholders to refine project goals, scope, and outputs iteratively.

• Write efficient, shareable code and documentation using tools like GitHub, IEX, and Confluence.

• Automate reporting tasks and build scalable dashboards to support data democratization.

• Communicate project goals, methodology, and insights to technical and non-technical audiences.

• Work with big data, applying best practices for data quality, query optimization, and pipeline development.

Experience and Qualifications:

• Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, or a related field or equivalent experience.

• 1–2+ years of experience in data analytics or a comparable role.

• Demonstrated ability to deliver data-driven insights that drive change or performance improvement.

• Intermediate proficiency in Python, R, or SQL for data analysis, transformation, and visualization.

• Experience with big data challenges and solutions.

• Strong critical thinking, problem-solving, and communication skills.

• Familiarity with inclusive design principles in data visualization.

• Business acumen and ability to frame business problems as analytical tasks.