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Introduction to the Team

Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.

We re hiring a hands-on high-performing individual contributor to own and evolve a core Vacation Rental KPI . You will be responsible for turning complex data into clear, actionable insights for senior leaders.

You will lead analysis projects end-to-end designing and building datasets, creating robust analytical products, and delivering high-impact dashboards and recommendations. You ll follow team-wide visualization standards and use AI/LLM tools pragmatically to create efficiency and scale.

In this role, you will:

Own a key KPI and its dashboard : Define, build, and maintain a stakeholder-facing dashboard that becomes the single source of truth for KPI health and performance.
Lead end-to-end analytics projects (scoping, data engineering, analysis, visualization, delivery) that drive measurable improvements in supply, quality, and conversion.
Build reliable, repeatable datasets and pipelines from multiple sources using SQL and scripting ( Python/R ), with strong attention to performance and data quality.
Create clear, persuasive visualizations and interactive dashboards (e.g., Tableau, Plotly, ggplot ) for both technical and non technical audiences, with a strong focus on storytelling and decision support.
High visibility : Own a core VR KPI and dashboard used by senior leaders to steer the VR business.
Direct, measurable impact : Your insights and recommendations will shape how we grow and optimize Vacation Rental supply.
Ownership and leadership : Lead analytics workstreams end-to-end, from problem framing to final recommendations and follow-through.
Modern toolkit : Work in a collaborative environment that embraces modern analytics, engineering, and AI tools to increase impact and scale.
Automate recurring reports and monitoring , including data-quality checks and alerting, to ensure stakeholders always have trusted, up-to-date views on key metrics.
Introduce and operationalize AI/LLM tools (e.g., for code generation, documentation, insight summarization, report automation) where they meaningfully increase productivity and scale.
Collaborate with product, marketing, operations, and data science teams to frame questions, translate business problems into analytical workstreams, and present trade-offs and recommendations.
Produce reproducible code and documentation , sharing artifacts via Git, Confluence , and team knowledge bases.
Apply statistical methods and intermediate ML approaches (e.g., regression, classification, clustering) when appropriate; partner with central Data Science to validate and scale models.
Design and analyze measurement strategies and experiments (A/B tests, pre/post analyses, causal impact, multivariate tests) for initiatives affecting VR inventory.

Experience & Qualifications:

Degree in Mathematics, Statistics, Computer Science, Economics, Engineering , or related field (Master's is a plus), or equivalent practical experience.
2-3 years in a comparable analytics or data science role (with relevant degree), or 4+ years of directly relevant industry experience.
Advanced SQL (joins, window functions, performance tuning).
Strong proficiency in Python or R for data wrangling, analysis, and automation.
Experience combining multiple data sources and building repeatable, well-documented datasets .
Visualization & storytelling: Solid experience designing and maintaining dashboards in Tableau or similar BI tools .
Ability to translate complex analyses and metrics into simple, intuitive visuals and narratives for non-technical stakeholders.
Statistics & experimentation: Working knowledge of applied statistics and basic ML (e.g., AB testing, statistical significance, regression, pre/post and causal impact analyses).
Data engineering mindset: Familiarity with data modeling , pipeline design, and best practices for performance, reliability, and data quality .
Communication & stakeholder management: Excellent written and verbal communication skills; able to listen, gather requirements , and proactively manage expectations.
Comfortable presenting findings and recommendations to senior and executive stakeholders .
Ways of working: Critical thinker with strong business acumen and a bias for action.
Collaborative mindset and willingness to coach junior colleagues and share best practices.
Familiarity with AI/LLM tools and enthusiasm for using them to automate workflows, speed analyses, and scale insight delivery.

Accommodation requests

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Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Data Scientist II - VR Performance Analytics

Job Description

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