Director, Machine Learning Science - Marketing

About the role

The Director of Machine Learning Science will lead the applied science team behind Expedia Group's Marketing organization. This team builds models and optimization systems that decide how Expedia bids on online advertising platforms and allocates marketing capital across channels and brands. The systems you own will directly shape the efficiency of one of the largest performance marketing programs in travel.

Responsibilities

• Own the strategy, roadmap, and OKRs for the machine learning systems powering Marketing
• Deliver production-grade ML models and optimization systems that improve bidding, capital allocation, and ROAS
• Apply rigorous experimentation and measurement to validate business impact
• Recruit, develop, and retain applied machine learning scientists and managers, and support their growth in a complex environment
• Prioritize the team's investment across platform migration, new capabilities, and model innovation
• Build partnerships across Product, Engineering, Finance, Analytics, and Marketing leadership, and align priorities with multiple product teams
• Navigate and influence the Expedia Group data platform and ML technology stack in line with company goals
• Contribute to the broader data science and analytics community across Expedia Group

Requirements

Minimum Qualifications:

• Graduate degree in machine learning, computer science, statistics, or a related quantitative field; or equivalent related professional experience
• 10+ years of relevant professional experience and 5+ years of people management experience, including leading high-performing machine learning teams
• Track record of delivering high-impact machine learning products from concept to production at scale
• Depth in supervised and unsupervised learning, statistics, and experimentation, including A/B testing, power analysis, Bayesian methods, and causal inference
• Command of the ML development lifecycle and MLOps: CI/CD, testing, observability, and reliable releases

Preferred Qualifications

• Domain experience in bidding, pricing, elasticity modeling, capital allocation, search, personalization, ranking, or recommendation
• Exposure to deep learning, LLMs, retrieval-based systems, and reinforcement learning
• Proficient programming skills: Python preferred, plus Java or Scala, and SQL or equivalent query languages
• Hands-on experience with ML and data engineering technologies such as Spark, Databricks, Kubernetes, and GPU compute
• Discipline in data and feature engineering (quality, lineage, documentation) and in model design with clear objectives, constraints, and risk guardrails
• Proficient communication, collaboration, and mentoring, with the ability to tailor complex concepts to technical and executive audiences

Benefits and Perks

• Medical, dental, and vision coverage
• Paid time off
• Employee Assistance Program
• Wellness and travel reimbursement
• Travel discounts
• IATAN membership

Pay

The total cash range for this position in Seattle is $224,000.00 to $313,500.00. Employees in this role have the potential to increase their pay up to $358,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Contact Information

For questions about this position, please contact [Contact Information]. For accommodation requests, visit this link.