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About This Role
Expedia Group brands power global travel for everyone, everywhere. We design cutting\-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.
Why Join Us?
To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.
We provide a full benefits package, including exciting travel perks, generous time\-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.
We create and deliver tailored marketing strategies for Expedia Group’s brands, focusing on establishing strong connections and cohesive experiences for travelers and partners. We leverage our functional expertise and creative excellence to build trust and loyalty for our brands through innovative marketing approaches and technology.
Expedia Group is seeking an innovative Data Scientist to transform how we understand and optimize organic search performance across SEO and AEO (AI\-enabled search). You'll build and maintain the AI and automation layer that powers performance intelligence for Expedia Group's retail brands including Expedia, Hotels.com, and Vrbo, enabling faster, deeper, and more scalable analysis without linearly scaling manual effort.
This role sits at the intersection of analytics, automation, and AI. You'll design agent\-assisted workflows, automate recurring performance analysis, build proactive anomaly detection systems, and create feedback loops that continuously improve how the team diagnoses performance drivers, identifies opportunities, and supports strategic decisions. You'll partner closely with marketing analysts and leadership to translate business questions into automated analytical workflows, leveraging tools like Claude, GPT, SQL, Python, and internal data platforms.
If you're passionate about using AI to make analytics teams more effective, not just faster at doing the same work, this is your opportunity to build the operating model for marketing performance in the age of AI.
In this role, you will:
- Design, build, and maintain an automation and AI layer for recurring performance workflows including weekly/monthly reporting, anomaly detection, and performance deep dives
- Develop agent\-assisted analytical workflows that accelerate root\-cause diagnosis, surface insights earlier
- Partner with performance analysts to translate business questions into reusable, automated frameworks that improve over time through feedback loops
- Create clear, actionable outputs (automated commentary, visualizations, structured insights) that reduce manual effort while maintaining analytical rigor and business context
- Support performance deep dives with rapid data exploration, segmentation analysis, and diagnostic workflows that combine domain knowledge with technical automation
- Continuously refine prompts, agent logic, and analytical outputs based on stakeholder feedback, changing KPIs, algorithm updates, and evolving business questions
Experience and qualifications:
- 2\+ years of experience in a highly analytical role (marketing analytics, data science, business intelligence, marketing automation, or comparable product analytics role)
- Bachelor's or Master's with analytical focus (Computer Science, Data Science, Mathematics, Economics, Statistics, etc.) or equivalent related professional experience
- Proven ability to translate ambiguous business problems into structured, repeatable analytical solutions
- Experience with marketing analytics platforms and datasets (Google Analytics, Adobe Analytics, Tableau, or similar BI tools); organic search (SEO/AEO) knowledge is a strong plus
- Results\-driven with an operational mindset, focused on building tools and systems that deliver sustained value, not just one\-off analyses
- Excellent communication and collaboration skills; able to work cross\-functionally with analysts, product managers, and business stakeholders to co\-design solutions
- Self\-directed learner who thrives in a fast\-paced environment and is comfortable iterating on solutions based on feedback and changing requirements
- Strong Skills in SQL and Python; comfortable building automated pipelines and integrating multiple data sources
Preferred qualifications:
- Demonstrated proficiency in AI and automation applications within analytics or marketing, specifically experience building workflows with GenAI to automate analysis, reporting, or insight generation.
- Hands\-on experience with prompt engineering, retrieval\-augmented generation (RAG), embeddings, or multi\-modal AI applications
- Familiarity with organic search (SEO) or agentic search (AEO) performance drivers, ranking systems, and key metrics
- Experience building or contributing to analytics platforms, data pipelines, or internal tools that scale analytical capabilities
- Background in growth marketing, performance marketing, or e\-commerce analytics
- Knowledge of advanced statistical or machine learning techniques applied to marketing measurement or optimization problems
The total cash range for this position in Seattle is $112,000\.00 to $156,500\.00\. Employees in this role have the potential to increase their pay up to $179,000\.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.
Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness \& travel reimbursement, travel discounts, and an International Airlines Travel Agent ( IATAN ) membership. View our full list of benefits .
Accommodation requests
If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request .
We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award\-winning culture by organizations like Forbes, TIME, Disability:IN, and others.
Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030\-50
Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs .
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E\-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I\-9 to confirm work authorization.
Salary Context
This $112K-$179K range is below the median for Data Scientist roles in our dataset (median: $157K across 236 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Expedia Group, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $198,000 based on 808 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($145K) sits 27% below the category median. Disclosed range: $112K to $179K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Expedia Group AI Hiring
Expedia Group has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, Data Scientist. Positions span Austin, TX, US, Seattle, WA, US. Compensation range: $179K - $318K.
Location Context
AI roles in Seattle pay a median of $227,400 across 1,084 tracked positions. That's 14% above the national median.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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