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Expedia Group

Senior Machine Learning Scientist - CRM Marketing

Reposted An Hour Ago
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Hybrid
Seattle, WA
173K-277K Annually
Senior level
Hybrid
Seattle, WA
173K-277K Annually
Senior level
The Senior Machine Learning Scientist will lead the development of ML systems for personalized CRM marketing, define technical roadmaps, and mentor team members while collaborating with cross-functional teams.
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At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.


Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Introduction to the Team

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.
 

This role is part of a focused machine learning science team within Marketing that builds the ML systems behind personalized CRM offers for Expedia Group’s travelers. Our models determine which customers to reach, when to engage them, and what incentive to offer — powering retention, reactivation, and growth campaigns that touch hundreds of millions of travelers worldwide. We continuously improve the algorithms that power campaign targeting - moving toward fully ML-driven personalization at scale - and this role will help define that technical roadmap.

 

In this role, you will:

  • Help define the ML science roadmap: Identify the highest-impact ML opportunities for CRM personalization, sequence initiatives against business strategy, and translate a multi-year vision into concrete, deliverable projects with clear milestones and measurable outcomes.

  • Build and own production ML systems: Lead the full lifecycle — from problem framing and metric design through data exploration, modeling, evaluation, deployment, and iteration — for systems that run daily at scale, in partnership with engineering.

  • Partner across the business: Work with marketing to understand customer and campaign objectives, with analytics to shape measurement strategies, and with engineering to deliver reliable production systems — bringing business acumen and domain depth to every technical decision.

  • Evolve experimentation and measurement: Strengthen how we test hypotheses and quantify impact — finding smarter, faster ways to validate ideas, reduce uncertainty, and build confidence in ML-driven decisions before and after they reach production.

  • Tell the data story: Communicate findings, trade-offs, and recommendations clearly to technical and business audiences through effective data visualization and narratives that influence priorities and build stakeholder confidence.

  • Raise the bar: Mentor scientists through code reviews and design discussions, drive adoption of modern AI tools and best practices, and champion standards for scientific rigor, reproducibility, and documentation.

 

Experience and Qualifications:

  • A Master’s or PhD in Operations Research, Applied Mathematics, Statistics, Economics, Computer Science, or a related quantitative field; or equivalent related professional experience

  • 6+ years (Master’s) or 4+ years (PhD) of experience applying machine learning to real-world problems, with a track record of delivering production ML systems that created measurable business impact

  • Proficiency across core ML methods (supervised, unsupervised, and statistical modeling) with demonstrated depth in at least one area relevant to this role

  • Strong experimentation and statistics fundamentals: designing rigorous experiments (A/B and beyond), selecting appropriate methods, and producing reliable, accurate analyses that inform high-stakes business decisions

  • Fluency in Python, SQL, and distributed data processing (Spark/Databricks), solid software engineering practices, and familiarity with modern AI development tools

  • Leader of cross-functional ML projects — aligning stakeholders on problem framing, success metrics, and delivery timelines — and can communicate findings clearly to both technical and non-technical audiences

 

Preferred:

  • Deep knowledge of constrained optimization, operations research, or budget allocation methods — designing systems that balance reach, relevance, and return on investment under real-world constraints

  • Deep understanding of causal inference — including the assumptions, limitations, and failure modes of observational methods — with experience applying these techniques to measure incremental effects in real-world settings

  • Experience with CRM personalization, loyalty marketing, incentive optimization, or customer retention systems

  • Experience with deep learning, reinforcement learning, or multi-armed bandits applied to real-world decision systems

  • Experience with customer lifetime value modeling, churn prediction, or propensity scoring

  • Hands-on ML production practices: CI/CD for ML, model monitoring, observability, and automated pipelines

The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, 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.


Benefits and perks

Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediagroup.com/life.


Accommodation requests

Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.


About Expedia Group

Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.


Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.


Equal Opportunity

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.

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