Staff Data Scientist, Listing Understanding

The Community You Will Join:

Listing Understanding Data Science develops a holistic understanding of listing attributes to enable better product experiences for guests and hosts. The team is focussed on using Computer Vision (CV) to understand the rich information available in photos and incorporating photos in a multimodal approach to listing understanding. You will work cross functionally with tech, product, and design organizations to develop and execute a roadmap for how photos are managed by hosts and enrich the guest experience.

The Difference You Will Make:

As the Staff DS in this space, you will ensure that we are deploying technologies for photo and listing understanding that meaningfully improve the guest and host experience. You will recommend and assess CV and multimodal approaches and ensure they are safe and effective. You will own data analysis of the connection between listing understanding and business impact. You will use a deep understanding of guest and host needs rooted in data to guide our technological and business roadmap. This is a hands-on role requiring expertise in prototyping, evaluation, and implementation of ML models and causal impact measurement.

A Typical Day:

Your contributions take a variety of shapes:

• Size business opportunities and develop the roadmap for investments in CV and multimodal listing understanding and integration into product experiences.
• Leverage photos and related structured and unstructured data to build and continuously improve listing understanding.
• Build causal models to understand how photos impact guest search and drive bookings and trip quality.
• Stay up to date with SoT models and prototype machine learning product features and iterate with engineering, product, and design.
• Develop and implement assessment frameworks for CV and multimodal modeling improvements to ensure that they are safe and effective.
• Measure the business value of our work through experimentation and causal analysis.

Your Expertise:

• 9+ years of industry experience in applied Machine Learning, with experience in Computer Vision, preferably including CLIP and ViT.
• Causal inference expertise, preferably with marketplace experience
• Advanced degree in Computer Science, Statistics, Econometrics or related field.
• Strong in XFN communication with partners in product, engineering, and design
• Expert in at least one programming language for data analysis (Python or R) with familiarity in SQL. Comfort with developing proof-of-concept prototypes. Passionate about AI and possessing a learner’s mindset towards LLMs and dynamic systems.
• Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection) and algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization)
• Proven ability to succeed in both collaborative and independent work environments
• Demonstrated willingness and track record of engagement with the technical community

Your Location

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [email protected]. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.