Senior Manager, Machine Learning Science - Fraud & Risk

Are you passionate about using machine learning to outsmart fraud and protect millions of travelers and partners worldwide? Would you like to work in the fast-paced, adversarial, high-scale, and data-rich world of online travel risk?

As Senior Manager, Machine Learning Science focused on Fraud & Risk at Expedia Group, you will lead a team of machine learning scientists building the models and AI systems that keep our marketplace safe from abuse while preserving a low-friction experience for legitimate customers.

The Fraud & Risk team plays a pivotal role in safeguarding the company’s finances, thwarting billions of dollars in fraudulent attacks annually. Our efforts extend beyond financial security: we effectively combat various threats, including phishing attacks, counterfeit vacation rental schemes, improper payment diversions, and unauthorized access to personal and payment card information. By ensuring a secure environment, we foster trust among travelers and providers, making Expedia’s sustained revenue growth possible.

We are looking for a highly technical ML leader with deep experience in supervised learning for tabular and text data, strong familiarity with unsupervised, sequential, and graph‑based methods, and a track record of shipping production ML systems. You and your team will own a portfolio of high‑impact ML products across Expedia’s fraud prevention landscape, partnering closely with product, engineering, and operations teams to design and ship real‑time decisioning systems. You are excited to evolve our team’s modeling approaches beyond our current baselines, raising the bar with modern methods such as sequence models, graph-based approaches, and research-driven GenAI techniques to dramatically improve performance and reduce manual queueing on complex fraud problems. You combine strong technical judgment with clear communication, stakeholder influence, and a passion for driving innovation on the team by growing talent, raising the quality bar, and building an inclusive, high‑performing culture in one of Expedia Group’s most dynamic and mission‑critical problem spaces.

In this role, you will:

• Lead, Mentor, and Develop: Mentor and grow a team of machine learning scientists, fostering a culture of innovation, collaboration and scientific rigor.
• Strategic Planning & Delivery: Define and manage the team's strategic roadmap, setting goals (OKRs) and aligning projects with broader business objectives in the online travel domain. Translate this roadmap into effective delivery of ML-drive features and products.
• Influence and Collaborate: Act as a key scientific leader, partnering with product, engineering, and business executives to align strategy and communicate complex technical concepts to a diverse audience.

Minimum Qualifications:

Experience & Education

• PhD or MS in a quantitative field (e.g., Computer Science, Economics, Statistics, Physics).
• 5 years of industry experience applying machine learning to solve real-world problems.
• 2 years of direct people management experience with a proven track record of hiring, mentoring, and developing a high-performing team of machine learning scientists.

Functional & Technical Skills:

Technical & Scientific Excellence:

• Deep expertise in machine learning theory, and learning algorithms (supervised and unsupervised), including a strong understanding of assumptions and limitations.
• Ability to design end-to-end ML solutions based on deep understanding of business requirements, including approach, algorithm choice, data strategy, deployment, and monitoring.
• Experience applying sequential models (e.g., RNNs, Transformers) and/or Graph Neural Networks (GNNs) in real-world settings, with awareness of their trade-offs and deployment considerations.
• Champion of software engineering best practices (e.g., version control, code reviews) within the team.
• Hands-on fluency in Python and its data science ecosystem (e.g., PySpark, scikit-learn), and SQL. Technical depth to unblock your team and contribute to architectural decisions.

Leadership & People Management:

• A passion for fostering healthy team culture that brings a balanced approach to individual team member career growth and collective goal of delivering impactful work.
• Demonstrated ability to lead, mentor, and grow ML/DS talent, fostering a culture of innovation, scientific rigor, and psychological safety.
• Strategic thinking and business acumen to align ML initiatives with organizational goals and measurable impact.
• Strong storytelling and influencing skills to build trust, drive alignment, and support high-stakes decisions.

Preferred Qualifications:

• Advanced domain knowledge in fraud, e-commerce, and operational applications of ML
• Hands-on experience building and deploying models using GenAI / LLM technologies (e.g., OpenAI, Anthropic Claude, Google Gemini, Hugging Face), including fine-tuning and prompt engineering for production use cases.
• Understanding of multi-agent architectures and best practices in agentic AI design and practical experience with function calling / tool use and API-based reasoning models to drive automated workflows.
• Experience with real-world AI evaluation techniques (golden sets, synthetic data generation, offline and interactive testing) for GenAI systems.