Director, Machine Learning Science - Marketing

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.

Expedia Group is looking for a Director of Machine Learning Science to lead the applied science team behind our Marketing organization. This team builds the models and optimization systems that decide how we bid on online advertising platforms and allocate 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.

You will lead scientists and managers delivering production ML at scale, own the roadmap, and partner closely with Marketing, Product, Engineering, Finance, and Analytics leadership. The role suits a leader who pairs technical depth with a broad business perspective and a record of measurable impact.

In this role, you will:

• Own the strategy, roadmap, and OKRs for the machine learning systems powering Marketing

• Design and 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 EG data platform and ML technology stack in line with company goals

• Contribute to the broader data science and analytics community across EG

Minimum Qualifications:

• Graduate degree in machine learning, computer science, statistics, or a related quantitative field; or equivalent related professional experience. PhD preferred

• 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

The total cash range for this position in Seattle is $ to $. Employees in this role have the potential to increase their pay up to $, 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…