Expedia Group is looking to solve complex business problems related to fraud and risk by developing and deploying machine learning models. The goal is to safeguard the company's finances, thwart fraudulent attacks, combat various threats like phishing and counterfeit schemes, and ensure a secure environment to foster trust and enable sustained revenue growth.
Requirements
- Experience applying sequential models (e.g., RNNs, Transformers) and/or Graph Neural Networks (GNNs) to solve real-world problems, with an understanding of their trade-offs and deployment considerations.
- Proficient in at least one major ML language (e.g., Python, Scala) with familiarity across others.
- Applies design principles, data structures, and patterns to write clean, modular, and pipeline-ready code.
- Deep understanding of supervised and unsupervised learning; working knowledge of self-supervised and reinforcement learning.
- Applies techniques like Bayesian Neural Networks, Markov Models, and Factor Analysis with awareness of assumptions and limitations.
- Conducts applied research and integrates findings from academic publications into practical solutions.
- Designs and implements custom evaluation techniques for tailored ML solutions.
Responsibilities
- Design, develop, and deploy machine learning models to solve complex business problems, ensuring alignment with strategic goals.
- Manage the full ML lifecycle—from data exploration and feature engineering to model evaluation, productionization, and monitoring.
- Partner with engineering, product, and business teams to ensure ML solutions are technically sound and business-relevant.
- Evaluate and implement cutting-edge algorithms and tools to enhance model performance, scalability, and robustness.
- Configure and optimize storage, compute, and pipeline environments (cloud, on-prem, clusters) to support scalable ML workflows.
- Contribute to the evolution of internal ML platforms, reusable components, and standardized methodologies.
- Present findings and recommendations through clear, data-driven storytelling and compelling visualizations tailored to diverse audiences.
Other
- Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field; or equivalent related professional experience
- 5+ years of experience building and deploying machine learning models in production environments.
- Demonstrates strong domain expertise (e.g., travel, retail) and critical reasoning aligned with business objectives.
- Provides technical mentorship and guides peers in frameworks and methodologies.
- Actively contributes to team learning through events, tools, and educational content.
