Expedia

29 сен

Machine Learning Scientist

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Рекламный баннер: ОБЩЕСТВО С ОГРАНИЧЕННОЙ ОТВЕТСТВЕННОСТЬЮ "ЦЕНТР НАЦИОНАЛЬНЫХ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ"

описание

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Senior Machine Learning Scientist - Search Marketing & Tech

We’re looking for a Senior Machine Learning Scientist to provide technical leadership within our Search Marketing & Tech organization at Expedia Group. This role is for someone who has demonstrated a track record of delivering high-impact ML projects from concept through production, partnering closely with engineering teams on multi-quarter initiatives that drive measurable business outcomes.

Our team builds and optimizes the ML models that power metasearch bidding and auction strategies across key partners (Google Hotel Ads, Trivago, Tripadvisor). As a senior technical leader, you will own end-to-end ML solutions for a domain area, define the technical roadmap, and drive the execution of complex projects that improve customer experiences and business performance at scale.

задачи

Technical Leadership & Ownership

Own end-to-end ML solutions within your domain, from problem framing and metric design through data exploration, model development, deployment, and post-launch iteration

Define technical direction for your area, including model architecture, system design, data contracts, and integration patterns with existing services

Lead multi-quarter ML initiatives in partnership with engineering, product, and business stakeholders, driving projects from ambiguous requirements to production systems at scale

Author technical blueprints and system designs that clearly outline objectives, constraints and trade-offs for complex ML systems

Model Development & Production

Design and implement production-grade ML models (e.g., gradient-boosted trees, deep learning, optimization algorithms, bandits/RL policies) that operate reliably under real-world constraints in collaboration with engineering.

Build robust training, evaluation, and serving pipelines with embedded observability, drift detection, and failure handling across the ML lifecycle

Enhance experimentation and measurement strategies, including A/B tests, causal inference methods, and long-horizon metrics to ensure models deliver durable impact as data and user behavior evolve

Cross-Functional Collaboration & Influence

Partner with engineering teams to translate ML designs into scalable, maintainable production systems, ensuring alignment on timelines, dependencies, and technical standards

Influence domain roadmaps by connecting ML opportunities to business objectives, articulating trade-offs, and building stakeholder alignment through evidence-based recommendations

Translate ambiguous business problems into clear ML formulations with measurable success criteria, balancing technical feasibility with business impact

Lead structured reviews with cross-functional partners, presenting complex technical concepts and trade-offs to both technical and non-technical audiences

Standards, Mentorship & Team Development

Raise the technical bar for the broader science community by codifying best practices, experimentation standards, and reusable patterns

Mentor other data and machine learning scientists, providing technical guidance through code reviews, design discussions, and knowledge sharing

Drive adoption of AI best practices

требования

Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or related quantitative field, or equivalent industry experience

6+ years (Master’s) or 4+ years (PhD) of hands-on experience applying machine learning to real-world problems

Demonstrated track record of leading at least one complex, multi-stakeholder production ML initiative that delivered measurable business impact

Technical Depth

Deep ML expertise in supervised and unsupervised learning, including tree-based methods, generalized linear models, and/or deep learning, with strength in feature engineering, regularization, calibration, and error analysis

Strong experimentation and statistics skills: designing and interpreting A/B tests, understanding bias/variance and statistical power, and applying causal inference techniques (e.g., diff-in-diff, IV, matching) where randomization is impractical

Fluency in Python and core data/ML libraries (pandas, NumPy, scikit-learn, PyTorch or TensorFlow), combined with solid software engineering practices (clean code, testing, version control, code review)

Proficient with large-scale data: strong SQL skills and familiarity with distributed data processing (e.g., Spark, Hive) for building training datasets, features, and analytical views

Leadership & Collaboration

Proven ability to lead through influence: aligning cross-functional stakeholders on problem definitions, success metrics, and rollout plans across multi-quarter projects

Strong communication skills: articulating technical concepts, trade-offs, and recommendations clearly to both technical and non-technical audiences

Experience with complex system diagnosis: combining logs, metrics, experiments, and domain intuition to identify root causes and drive data-informed remediation plans

Experience with ads, auctions, marketplace optimization, or bidding systems (e.g., CPC/CPA bidding, budget pacing, ranking, ROI optimization, Controllers)

Familiarity with multi-objective or constrained optimization problems, balancing competing objectives (e.g., profit, volume, ROI) using modeling, heuristics, or RL/bandit methods

Hands-on experience with modern ML production practices: feature stores, model registries, CI/CD for ML, automated monitoring and alerting

Experience shaping team-level technical direction: proposing and prioritizing ML investments, identifying reusable components, and defining standards for experimentation and documentation

Exposure to causal inference or advanced experimentation techniques in noisy business environments (e.g., geo-based tests, synthetic controls, uplift modeling)

Experience with AI/ML-driven systems, including exposure to large language models or foundation model fine-tuning and evaluation

условия

Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.

Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.

навыки

python pandas numpy scikit-learn pytorch tensorflow sql spark ci/cd

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