Director, Machine Learning Science - Marketing

Position

Director, Machine Learning Science – Marketing

• Own the strategy, roadmap, and OKRs for the machine learning systems powering Marketing.
• Design and deliver production-graded 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, supporting 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, aligning 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.

• Graduate degree in machine learning, computer science, statistics, or a related quantitative field;
  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.

• 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 in 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.

Target salary range in Seattle: $224,000 – $313,500, with potential to increase up to $358,500 based on performance.

We offer comprehensive medical, dental and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and membership in the International Airlines Travel Agent Network.

May 2024:
Equal Opportunity. 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 and, if necessary, the Department of Homeland Security with information from each new employee's I-9 to confirm work authorization.