Senior ML Scientist: CLV & Business Impact

11105 Expedia, Inc.; Austin (TX); On-site; USD 138,000 - 193,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

PTO and EAP

Travel reimbursement

IATAN travel discounts

Job summary

Expedia Group is advancing a high-impact CLV prediction initiative. As a Machine Learning Scientist III, you’ll lead scalable ML/DS work end-to-end and collaborate across product, engineering, marketing, and more to maximize long-term traveler value.

You’ll influence foundational modeling decisions, work with cross-functional teams, and help shape the research direction in a fast-paced environment.

Qualifications

• Advanced degree in Computer Science, Statistics, Operations Research, Econometrics, Economics, or related field.
• 3–5+ years of professional experience; equivalent project or research experience accepted.
• Hands-on experience building large-scale prediction models with advanced deep learning like transformers.
• Ability to analyze large datasets and derive actionable insights.

Responsibilities

• Lead research and implementation of scalable ML/data-science solutions end-to-end with engineering rigor.
• Apply causal analysis to understand drivers of customer lifetime value and signals affecting CLV.
• Design/back-test methods to evaluate model performance in development and production.
• Translate findings into actionable insights for technical and non-technical stakeholders.
• Break down ambiguous business requirements into data-driven solutions.
• Stay informed on ML/AI research with internal learning resources and collaboration.

Skills

Python

Deep learning

Transformer models

Big data

Data analysis

Education

Advanced degree in CS/Statistics

Tools

Spark

Job description

Expedia Group is advancing a high-impact CLV prediction initiative. As a Machine Learning Scientist III, you’ll lead scalable ML/DS work end-to-end and collaborate across product, engineering, marketing, and more to maximize long-term traveler value.

You’ll influence foundational modeling decisions, work with cross-functional teams, and help shape the research direction in a fast-paced environment.