Data Scientist II, Analytics

Expedia Group•Seattle, WA

20h•$112,000 - $156,500•Hybrid

About The Position

The Data Scientist II role is on Expedia Group’s Commercial Partnerships Analytics team within its B2B division. The team supports partnerships across the Americas spanning two products, including the business’s largest partnership. The role applies statistical techniques and AI to partnership analytics, combining detailed analysis with an understanding of broader business context and macro trends to help grow these partnerships. The position involves independently working with structured data and, with guidance, unstructured data. The data scientist performs descriptive and inferential analyses, provides recommendations, manages small analytics projects, and communicates insights to technical and non-technical stakeholders. The role is available only in Seattle and follows a flexible work model requiring employees to work in the office at least three days per week.

Requirements

Experience applying statistical or analytical methods to business, product, customer, or partner questions.
Experience with SQL and proficiency in Python, R, or a similar programming language.
Understanding of descriptive statistics, inferential analysis, experiment design, and statistical concepts.
Experience validating AI work and end products, in addition to using AI.
Experience cleaning, joining, validating, and analyzing structured data from multiple sources.
Ability to translate business questions into measurable metrics and analytical approaches.
Ability to communicate insights clearly through written summaries, visualizations, dashboards, and presentations.
Ability to manage small projects and collaborate with technical and non-technical stakeholders.
Bachelor’s degree in statistics, mathematics, computer science, data science, economics, or a related technical field, or equivalent related professional experience.

Responsibilities

Clean, query, combine, and validate structured data independently, and work with unstructured data under guidance, using SQL and/or Python.
Manage timelines and priorities for small analytics projects while building trust and credibility with stakeholders.
Perform descriptive and inferential analyses independently in a business context and recommend next steps.
Communicate insights and recommendations to technical and non-technical stakeholders through clear visualizations and presentations.