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Machine Learning Scientist III - VRBO PricingTraveltechessentialist • Austin, Texas, United States
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Machine Learning Scientist III - VRBO Pricing

Traveltechessentialist
  • US
    Austin, Texas, United States
  • US
    Austin, Texas, United States
Postuler Maintenant

À propos

Expedia Group brands power global travel for everyone, everywhere. We design cutting‑edge technology to make travel smoother and more memorable, and we create groundbreaking solutions for our partners.
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 when one of us wins, we all win. We provide a full benefits package, including travel perks, generous time‑off, parental leave, flexible work options, and career development resources.
About the Role The Machine Learning Science team is building a scalable and robust system to enable pricing as a lever to optimize business performance. As a Machine Learning Scientist III, you will research and build this pricing system, working on end‑to‑end pricing problems and contributing to active research areas such as causal inference, operations research, demand estimation, and experiment design with spillovers. Your models will be deployed to production and evaluated via A/B testing.
In this role you will:
Apply solid scientific skills, strong analytical and innovative thinking to quickly learn new domains and turn ideas into working solutions.
Articulate technical solutions and plans to stakeholders based on detailed understanding of business requirements.
Research and implement scalable machine‑learning and data‑science solutions end‑to‑end with engineering rigor.
Follow the latest technology and research and customize them to our problem space.
Design success metrics for both short‑term and long‑term performance.
Guide solutions using data insights based on deep understanding of business domains.
Collaborate with other machine‑learning and data‑science teams to build a great data‑science culture in Expedia Group.
Experience & Qualifications
3+ years industry experience and an advanced degree (PhD preferred) in a quantitative field such as statistics, operations research, economics, computer science, or equivalent.
Expertise in one or more areas of machine learning, causal inference, and operations research.
Comfortable analyzing complicated data sets to generate insights guiding solution development.
Passion for solving real‑world problems using principled techniques.
Focus on problem solving with pragmatic methods.
Understanding of modern machine‑learning and data‑science techniques and their mathematical underpinning.
Strong communication skills, able to convey ideas clearly to partners of varying technical levels.
Collaborative team player, building trust with stakeholders.
Proficiency in Python, Scala, or similar.
Experience with the big‑data ecosystem (Hadoop/Spark).
Experience in pricing is a plus.
Experience with large‑scale marketplace experiment design and analysis is a plus.
Compensation The total cash range for this position in Austin is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00 based on ongoing, demonstrated, and sustained performance. Starting pay will vary based on location, budget, and individual skills.
Benefits We offer medical/dental/vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursements, travel discounts, and an International Airlines Travel Agent membership.
Equal Employment Opportunity Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E‑Verify.
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  • Austin, Texas, United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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