Director, Machine Learning Science - Marketing

Expedia•Seattle, WA

About The Position

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.

Requirements

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
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

Nice To Haves

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

Responsibilities

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