Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.
Prepare for senior DS depth on metrics, abuse/fraud intuition, and shipping models:
Strong fit if you ship production ML for risk/trust at marketplace scale and care about precision–recall under real user harm. Remote-friendly listing; thin salary and review data means you should verify comp and team scope with Airbnb recruiters.
As a Senior Data Scientist, Trust (Inference) at Airbnb, a typical day centers on models that score risk and authenticity at booking and hosting touchpoints: feature review, offline evaluation, online inference latency/quality checks, and partnering with Trust product and engineering on threshold changes. Expect experiment design, metric reviews for fraud/abuse signals, and production handoff of models that must stay reliable under marketplace traffic.
Role-shaped focus areas (no cert package in source data):
The listing location is “Anywhere in the World” with remote flagged, so work is not tied to a single city in the provided data.
It points to production models that score trust/safety signals at request time—latency, monitoring, and decision quality matter as much as offline AUC.
See Wikipedia’s Airbnb page for founding, marketplace model, and public-company context (ticker ABNB).
Website: airbnb.com
Airbnb, Inc. is an American company operating an online marketplace for short-and-long-term homestays, experiences and services in various countries and regions. It acts as a broker and charges a commission from each booking. Airbnb was founded in 2008 by Brian Chesky, Nathan Blecharczyk, and Joe Gebbia.
Public cache only — not an employee review.
Senior Data Scientist, Trust (Inference) | Airbnb | Anywhere in the World Position Summary The Platform Data Science team at Airbnb is seeking a Senior Data Scientist to join our efforts in safeguarding guest and host trust. You will be responsible for detecting and defending against adversarial behavior, such as fraudulent listings, fake inventory manipulation, review and content manipulation, account takeover, and other bad-actor activities on the platform. Your work will directly impact the safety, smartness, and personalization of Airbnb experiences. Key Responsibilities Own rigorous statistical thinking and applied ML to measure the impact of new listing integrity defenses, model risk at the listing or account level, and evaluate enforcement policies. Partner closely with product, engineering, policy, and operations teams across Trust to ensure guest and host trust is maintained. Conduct experiments and causal inference to drive product evolution and business outcomes. Develop scalable intelligence systems that enhance the overall user experience on Airbnb. Who We're Looking For Rigorous statistical thinker with a strong background in machine learning and data science. Experience in causal inference, experimentation design, and risk modeling. Aptitude for working with large datasets and developing scalable solutions. Strong communication skills to effectively collaborate across teams. More About Airbnb At Airbnb, our real innovation is not allowing people to book a home; it's designing a framework to allow millions of people to trust one another. Trust is the energy source that drives Airbnb. Our mission is to make the world more connected through unique travel experiences. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. Applying for This Role To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there.
Generated for personal interview prep · 2026-08-07 UTC · getajob.ai