Job Description

Overview

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.

We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees\' passion for travel and ensure a rewarding career journey. Were building a more open world. Join us.

Introduction to team:

Are you passionate about using machine learning to improve Customer Experience? Would you like to work in the fast-paced, competitive, customer-focused, and data-rich world of online travel?

Our Machine Learning and Data Science team are growing! We are looking to hire researchers and data scientists interested in breaking new ground to tackle some of the most complex customer experience problems in the travel domain. The focus of your job will be on developing state-of-the-art machine learning algorithms and Generative AI solutions to power and enhance the customer experience across highly complex post-booking recommendations, customer service, and trip management use cases. You will tackle substantial technical challenges, from inference problems arising from long-tail traveler data to multi-objective optimization problems in the highly dynamic, operationally complex environment of customer service. Your passion for the craft of statistics, machine learning, and causal inference will unlock tangible growth for our business by exploiting these rich data sets and building effective solutions for travelers and our partners.

This is your opportunity to build the core algorithms that help Expedia Group\'s Post Booking organization bring context and intelligence to every step of the traveler journey and redefine what service excellence in travel can be. We are looking for a hands-on principal scientist to help us build and execute on a high-impact vision, tackling fundamental challenges in predictive modeling and Generative AI to improve customer satisfaction and loyalty, lower cost-to-serve, and make travel more seamless for millions of customers and partners worldwide.

What we\'re looking for

Machine Learning Engineering

• Configure, maintain, and optimize storage and processing environments (cloud, on-premises, cluster management, etc.).
• Build production-grade data and machine learning pipelines that support batch and streaming applications.
• Advocate for software design best practices and demonstrate your ability to construct robust data and machine learning pipelines.

Machine Learning / Data Science

• Perform applied research to consistently achieve desired solution performance and improve organizational capabilities.
• Demonstrate an in-depth understanding of all aspects of learning theory.
• Support leaders in setting up frameworks for the machine learning development lifecycle and devise machine learning strategies.
• Advise business leaders in complex settings to create and enable robust machine learning solutions with high impact, at an expert level.
• Lead and mentor others in all machine learning activities.

Generative AI

• Deep expertise in LLM fine-tuning and prompt engineering (e.g., OpenAI APIs, Hugging Face, Anthropic Claude, Google Gemini).
• Strong experience with AI orchestration tools (e.g., LangChain, LlamaIndex, vector databases for retrieval augmentation).
• Hands-on knowledge of function calling and API-based reasoning models (e.g., using structured outputs to drive automated workflows).
• Proficiency in Python and AI development frameworks for building scalable AI applications.
• Understanding of multi-agent architectures and best practices in agentic AI design.
• Experience with real-world AI evaluation techniques, including golden sets, synthetic data generation, and interactive testing

Statistics

• Leverage a solid theoretical foundation and apply advanced statistical methods to a broad range of problems.
• Demonstrate experience in advanced experimental design (e.g., adaptive designs).
• Read relevant publications in the field and implement described methods to business problems.
• Act as a technical mentor for junior profiles.

Model Design

• Design end-to-end models based on a detailed understanding of business requirements, including general approach, choice of algorithm, and data sources.
• Ensure model output reflects a deep understanding of business requirements, adhering to standard methodologies, academic research, and experience.
• Exhibit expert knowledge of complex model design, incorporating the latest academic and published research, including neural networks, transformers, and reinforcement learning domains.
• Display advanced domain knowledge (e.g., travel, online retail), business acumen, and critical reasoning skills.
• Demonstrate a critical understanding of business processes and challenges to recommend and develop solutions that meet unique business needs and achieve objectives.

Visualization

• Embed visualizations from tools utilizing basic techniques (e.g., iframes).
• Demonstrate proficiency in visualization tools and create complex calculations using advanced features.
• Apply data visualization principles consistently, resulting in clear and consistent outcomes.
• Build complex charts with limited supervision.
• Effectively use color palettes, considering double encoding and end-user fatigue, and create clear and consistent visualizations with expert use of typography.
• Demonstrate familiarity with UX and UI concepts, such as padding, framing, chart placement, white space balance, and hierarchy of elements.
• Create complex calculations using advanced features in Expedia Group\'s visualization tooling capabilities.

Communication and Presentation

• Be a persuasive storyteller, using influencing techniques that build trust with teams and partners, and establish long-term relationships.
• Contribute ideas and participate in industry events and forums, recognized as an inspiring leader outside the company.
• Drive a culture of constructive critique, challenging others to bring fresh and creative perspectives to differentiating functional technical communications.
• Creatively develop tools, visual aids, and original content to support the understanding and education of sophisticated and technical information (e.g., legal, operational risk, and regulatory data).
• Make recommendations for business process improvement, sponsor and stage workshops/knowledge sessions to improve the organization\'s functional knowledge and acuity, and leverage insights and subject matter experts to overcome challenges.

Stakeholder and Project Management

• Expertly solve the most complex questions and challenges, showcasing analytical mastery externally.
• Mentor and train others on analytical problem-solving, project management, and influencing for business impact.
• Manage stakeholders with frequent communication and expectation management, meeting deadlines and minimizing surprises.
• Manage the backlog effectively, including across large cross-functional teams, delivering projects to maximize business impact in sync with business timing.

Minimum Qualifications

• Bachelor\'s, Master\'s, or Ph.D. degree in a technical field or equivalent related professional experience.
• Expertise in more than one major ML programming language (Python, R, Scala, etc.) and familiarity with others.
• Experience leading large data science technical programs, delivering successful outcomes typically involving cross-functional teams of 10+.
• Demonstrated ability to regularly contribute to the data science and technology community through blog posts, tech talks, major data science or technology domain conferences/events, etc.
• Experience defining data science best practices at a team/capability level.
• Expertise in configuring, maintaining, and optimizing storage and processing environments (cloud, on-premises, cluster management, etc.).
• In-depth understanding of all aspects of machine learning theory.
• Strong experience in application in an industrial setting and crafting robust solutions relatively quickly.
• Solid theoretical foundation applies advanced statistical methods to a broad range of problems.
• Experience with advanced methods such as Stochastic Processes, Bayesian Neural Networks, Markov Models, Discriminant and Factor Analysis, and applies them while considering underlying assumptions and limitations.
• Continuous learning and adaptability to stay ahead of rapidly evolving technologies and techniques in machine learning and data science.
• Strong communication and storytelling skills to effectively convey complex technical concepts to diverse stakeholders.
• Collaborative mindset and ability to lead cross-functional teams in delivering innovative solutions.
• Strategic thinking and business acumen to align machine learning initiatives with organizational goals and drive measurable impact.
• Ethical and responsible AI practices to ensure fairn]]>

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