Data Scientist
About The Company Airbnb was founded in 2007 when two hosts welcomed three guests to their San Francisco home. Since then, the company has experienced remarkable growth and now boasts over 5 million hosts worldwide who have welcomed more than 2 billion guest arrivals across nearly every country on the planet. Airbnb’s platform offers unique stays and experiences that foster authentic connections between guests and local communities, revolutionizing the hospitality industry and creating a global community centered on sharing and belonging.
About The Role We are seeking a highly skilled and experienced Data Scientist to join our Listing Understanding Data Science team. In this role, you will focus on leveraging computer vision and multimodal data approaches to enhance the understanding of listing attributes, particularly through analyzing photos. Your work will directly impact the guest and host experience by developing innovative machine learning models and causal inference frameworks that improve listing quality, search relevance, and overall platform engagement. You will collaborate cross-functionally with product, engineering, and design teams to develop and execute strategies that utilize visual and structured data to optimize listing insights. This hands-on position requires expertise in prototyping, evaluating, and deploying machine learning models, as well as measuring their business impact through rigorous experimentation and causal analysis.
Qualifications
- 9+ years of industry experience in applied Machine Learning, with a focus on Computer Vision
- Experience with models such as CLIP, ViT, or similar architectures
- Expertise in causal inference, preferably within marketplace or platform environments
- Advanced degree in Computer Science, Statistics, Econometrics, or related field
- Proficiency in programming languages such as Python or R, with familiarity in SQL
- Experience developing proof-of-concept prototypes and deploying ML solutions
- Deep understanding of machine learning best practices, including feature engineering, model selection, and A/B testing
- Strong communication skills to collaborate effectively with cross-functional teams
- Passion for AI, continuous learning, and staying current with emerging technologies like LLMs and dynamic systems
- Proven ability to work independently and as part of a collaborative team
- Active engagement with the technical community and a track record of innovation
Responsibilities
- Identify and size business opportunities related to visual and listing understanding, developing strategic roadmaps for investment in computer vision and multimodal approaches
- Utilize photos and structured/unstructured data to enhance listing understanding models continuously
- Build causal models to analyze how photos influence guest search behavior, bookings, and trip quality
- Prototype, evaluate, and iterate on machine learning features in collaboration with engineering, product, and design teams
- Develop assessment frameworks to ensure the safety, effectiveness, and fairness of CV and multimodal models
- Measure the business impact of models and features through experimentation, causal analysis, and data-driven insights
- Stay updated with state-of-the-art models and incorporate them into product features
- Communicate findings and technical insights effectively across teams to inform product development and strategic decisions
Benefits
- Competitive salary and performance-based bonuses
- Equity options and stock grants
- Comprehensive health, dental, and vision insurance plans
- Flexible work arrangements, including remote work eligibility
- Paid time off, holidays, and parental leave
- Learning and development programs to support continuous growth
- Employee travel credits and discounts
- Inclusive and diverse work environment that values innovation and collaboration
Equal Opportunity
Airbnb is committed to fostering an inclusive and diverse workplace. We believe that a broad spectrum of perspectives and experiences drives innovation and enhances our ability to serve our global community. We encourage all qualified individuals to apply, regardless of race, gender, age, disability, sexual orientation, gender identity, or background. We also strive to provide a disability-inclusive application and interview process.