{"id":1506552,"url":"https://alion.io/job/expedia-group-senior-machine-learning-scientist","title":"Senior Machine Learning Scientist","company":{"id":1763687,"name":"Expedia Group","domain":"expediagroup.com","url":"https://alion.io/company/expediagroup-com","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":4,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":14,"computed_at":"2026-10-02T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":118000,"max_usd":238000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":21},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"ClearML","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"bandit","optional":true},{"name":"CI/CD","optional":true},{"name":"Feature Store","optional":true},{"name":"Fine-tuning","optional":true}],"status":"live","first_seen_at":"2026-09-29T00:00:00Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-02T16:43:59Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"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.\nHere, 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.\nSenior Machine Learning Scientist - Search Marketing & Tech\nWe’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.\nOur 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.\nIn this role, you will:\nTechnical Leadership & Ownership\nOwn end-to-end ML solutions within your domain, from problem framing and metric design through data exploration, model development, deployment, and post-launch iteration\nDefine technical direction for your area, including model architecture, system design, data contracts, and integration patterns with existing services\nLead multi-quarter ML initiatives in partnership with engineering, product, and business stakeholders, driving projects from ambiguous requirements to production systems at scale\nAuthor technical blueprints and system designs that clearly outline objectives, constraints and trade-offs for complex ML systems\nModel Development & Production\n 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.\nBuild robust training, evaluation, and serving pipelines with embedded observability, drift detection, and failure handling across the ML lifecycle\nEnhance 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\nCross-Functional Collaboration & Influence\nPartner with engineering teams to translate ML designs into scalable, maintainable production systems, ensuring alignment on timelines, dependencies, and technical standards\nInfluence domain roadmaps by connecting ML opportunities to business objectives, articulating trade-offs, and building stakeholder alignment through evidence-based recommendations\nTranslate ambiguous business problems into clear ML formulations with measurable success criteria, balancing technical feasibility with business impact\nLead structured reviews with cross-functional partners, presenting complex technical concepts and trade-offs to both technical and non-technical audiences\nStandards, Mentorship & Team Development\nRaise the technical bar for the broader science community by codifying best practices, experimentation standards, and reusable patterns\nMentor other data and machine learning scientists, providing technical guidance through code reviews, design discussions, and knowledge sharing\nDrive adoption of AI best practices\nExperience & Qualifications:\nMaster’s or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or related quantitative field, or equivalent industry experience\n6+ years (Master’s) or 4+ years (PhD) of hands-on experience applying machine learning to real-world problems\nDemonstrated track record of leading at least one complex, multi-stakeholder production ML initiative that delivered measurable business impact\nTechnical Depth\nDeep 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\n 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\n 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)\n 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\nLeadership & Collaboration\nProven ability to lead through influence: aligning cross-functional stakeholders on problem definitions, success metrics, and rollout plans across multi-quarter projects\nStrong communication skills: articulating technical concepts, trade-offs, and recommendations clearly to both technical and non-technical audiences\nExperience with complex system diagnosis: combining logs, metrics, experiments, and domain intuition to identify root causes and drive data-informed remediation plans\nPreferred Qualifications\nExperience with ads, auctions, marketplace optimization, or bidding systems (e.g., CPC/CPA bidding, budget pacing, ranking, ROI optimization, Controllers)\nFamiliarity with multi-objective or constrained optimization problems, balancing competing objectives (e.g., profit, volume, ROI) using modeling, heuristics, or RL/bandit methods\nHands-on experience with modern ML production practices: feature stores, model registries, CI/CD for ML, automated monitoring and alerting\nExperience shaping team-level technical direction: proposing and prioritizing ML investments, identifying reusable components, and defining standards for experimentation and documentation\nExposure to causal inference or advanced experimentation techniques in noisy business environments (e.g., geo-based tests, synthetic controls, uplift modeling)\nExperience with AI/ML-driven systems, including exposure to large language models or foundation model fine-tuning and evaluation\nAccommodation requests\nExpedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request athttps://expedia.service-now.com/askeg?id=job_accommodation.\nAbout Expedia Group\nExpedia 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.\nImportant notice\nEmployment 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/.\nEqual Opportunity\nExpedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.","description_format":"text","description_chars":8084,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commerce","Travel & Tourism","Marketplaces"],"lifecycle":[{"event":"open","at":"2026-09-30T06:02:52Z"}],"liveness":{"score":88,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.878,"p_room":1,"age_days":3,"expected_fill_days":14,"reasons":["conf:3","velocity","win:early","comp:brand"],"computed_at":"2026-10-02T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/expedia-group-senior-machine-learning-scientist","json_url":"https://alion.io/job/expedia-group-senior-machine-learning-scientist.json","meta":{"generated_at":"2026-10-03T02:01:00Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2073,"day_limit":5000,"remaining_today":2927,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}