Machine Learning Scientist II

Introduction to the Team

Are you excited by the opportunity to Power global travel for everyone, everywhere? Do you want to redefine the way people plan, search for, and book their travel?

We create and deliver tailored marketing strategies for Expedia Group’s brands, focusing on establishing strong connections and cohesive experiences for travelers and partners. We leverage our functional expertise and creative excellence to build trust and loyalty for our brands through innovative marketing approaches and technology.

At Expedia Group, we believe that travel brings the world together, and we are passionate about the endless possibilities. This role is a great opportunity join our EG Organic and Agentic Search team, which is working to design and build ML solutions and GenAI products that dynamically and efficiently provide the right information to travelers, while driving substantial growth in organic traffic and overall shopping conversion through the synergistic use of Data, AI, and Technology.

Success in this role is fueled by your innovative contributions to our automation products. You'll be instrumental in advancing machine learning methodologies to tackle complex business challenges. Your crucial skills include independently assessing model performance, crafting end-to-end solutions, and effectively communicating compelling rationales. Your proficiency in refining and optimizing practices, methodologies, and tools for the SEO team is pivotal for driving continuous improvement.

You will collaborate closely with Machine Learning scientists, Data Scientists, Software Engineers, SEO Specialists, Data Engineers, Product Managers, Senior Leaders, and other business stakeholders across various Expedia Group locations worldwide.

In this role, you will:

• Build, maintain, and evaluate machine learning models using supervised, unsupervised, and reinforcement learning techniques, with support in model selection, regularization, and performance evaluation.

• Extract and combine data from multiple sources, and write clean, maintainable, modular code using Python, Java, SQL, or similar ML focused languages.

• Conduct context engineering, apply statistical methods, design experiments, and choose appropriate analytical approaches based on model assumptions, business objectives, and data constraints.

• Build GenAI solution to drive organic traffic acquisition and better traveler progression on landing pages. Using machine learning to continuously improve relevance, readability, factual accuracy and alignment with search intent – ensuring editorial content drives organic traffic and engagement.

• Understand and articulate model design decisions, including algorithm choice, evaluation approach, and data sources, while engaging with the research community to apply relevant innovations.

• Apply visualization and UX principles to produce clear, consistent charts, build complex visualizations with minimal supervision, and embed outputs using common visualisation tools.

• Communicate technical concepts clearly to technical and nontechnical partners, craft well-structured presentations, anticipate questions, and tailor messaging to different audiences.

• Collaborate across teams, contribute to documentation and communication materials, share findings with peers and leaders, and proactively support crossfunctional alignment.

• Frame business problems as data science tasks, manage project backlogs, deliver work that aligns with business timelines, and remain persistent and creative when facing roadblocks.

• Demonstrate strong business understanding, connecting organisational processes and challenges with data science opportunities to maximise impact.

Experience and qualifications:

• Bachelor's or master's degree in a quantitative field such as mathematics, physics, engineering, operations research, data science or similar

• 1-3 years of experience in industry or equivalent

• Strong proficiency with Python / Pyspark and SQL.

• Demonstrated ability to build and maintain multiple data science project/product in production environments.

• Extensive experience one or more of the following: advanced statistical techniques for A/B testing, multi-armed bandit testing, methods for experimental design, observational causal inference, or quasi-experimental analysis

• Record of accomplishment for executing independent projects and leading complex, multi-functional projects with several dependencies.

• You understand the concepts and steps involved in working with real-world large data sets: from domain-specific problem understanding, data preparation, travel-related data processing, data integration, data structures for ML, data pipelining, data modeling, and AI/ML algorithms; strong data science knowledge and skills.

• Advanced proficiency in GitHub for collaborative development and version control

• Proficient in cloud computing, specializing in big data applications and leveraging MLOps for streamlined machine learning model deployment.

• You have proven knowledge of ML techniques such as Neural Networks, XGBoost, Bayesian methods, clustering, decision trees, random forests, NLP, etc., excellent grasp of statistical concepts and methods.

• You have a passion for solving problems and finding patterns and insights within structured and unstructured data

• GenAI/LLM experience is a bonus