The Product Team creates high-quality end-to-end experiences for travelers, partners, and Expedia Group. Our focus on customer-centric innovation enables us to develop products that build loyalty and repeat business. We partner closely with teams across Expedia Group to drive growth and achieve results for our customers and the company.

We are looking for a Data Scientist III, Product Analytics to partner closely with product, design, and engineering to drive decisions across our membership and loyalty experiences. This is an established IC role that independently owns analytics for one or more product areas, applying strong product thinking, experimentation, and storytelling skills with a moderate level of guidance.
The role regularly interacts with stakeholders up to Senior Director level and is expected to influence strategy through clear, data backed recommendations.

In this role, you will:

Partner with product teams to clarify business problems, define success metrics, and translate ambiguous questions into structured analytical plans.
Design, run, and analyze experiments (A/B tests, pre/post, quasi experimental reads) to measure impact, quantify trade offs, and guide iteration.
Perform deep dive product analysis (funnels, cohorts, segmentation, sizing) to uncover drivers of performance and identify opportunities for growth and customer experience improvements.
Build reliable datasets and dashboards using SQL and modern BI tools, enabling self serve product performance monitoring across platforms (web, app, partner).
Apply solid statistical thinking (probability, sampling, inference, regression) to ensure reads are robust, distinguish signal from noise, and clearly communicate caveats.
Use Python/R (or similar) to prototype models and advanced analyses when needed (e.g., regression, clustering, simple prediction) and to automate recurring analytics workflows.
Tell clear, compelling stories that move stakeholders from insight to action framing context, methods, results, and recommendations for both technical and non technical audiences.
Champion data quality and reproducibility by following best practices for data validation, query performance, version control, and documentation.
Collaborate and upskill others by seeking peer review, sharing best practices, and providing light mentorship to more junior analysts or data scientists.

Experience and qualifications:

5+ years of experience in analytics, product analytics, or data science roles.
Bachelor s or Master s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics, Engineering) or equivalent practical experience.
Proven track record of delivering data driven insights and recommendations that influenced product decisions or drove measurable performance improvements.
Strong SQL : able to work confidently with large, complex datasets; write intermediate queries (joins, subqueries, CASE logic, window functions, unions); and optimize for performance and cost.
Experience with at least one scripting language such as Python or R for analysis, modeling, and automating recurring tasks.
Experimentation and statistics : comfortable with hypothesis testing, confidence intervals, experiment design, and interpreting regression/logistic regression outputs.
Hands on experience with A/B testing platforms and understanding of when to use experiments vs. observational or exploratory analysis.
Data visualization and dashboarding skills (e.g., Tableau, Power BI, or similar) with a focus on clarity, appropriate chart selection, and inclusive design basics (e.g., color use, accessibility).
Ability to build and validate basic models (e.g., linear/logistic regression, simple clustering) and understand data/feature requirements and key assumptions.
Demonstrated product sense : ability to connect metrics to customer journeys, refine problem statements, and propose pragmatic analytical approaches aligned with business timelines.
Experience defining or refining product KPIs , building scorecards, and monitoring performance for ongoing features and launches.
Strong critical thinking and problem solving skills; able to break complex problems into manageable analytical steps and iterate based on learnings.
Excellent communication and influencing skills comfortable presenting to PMs, engineers, designers, and senior leaders, and adapting depth/rigor to the audience.
Collaborative working style, with a proactive, ownership oriented mindset and openness to feedback, peer review, and continuous learning.

Data Scientist III, Product Analytics

Job Description

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