Jobs / United States / Airbnb
Data Scientist - Algorithms, Community Support
Airbnb · 🇺🇸 Remote - USA · Remote
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 167 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 71 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Airbnb paid sponsored hires in similar roles19 certified filings for “Data Scientist” (Data Scientists) in CA: $151k–$191k, median $177k. Most were filed at wage level II (37%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Airbnb
The US Department of Labor certified 167 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 71 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Airbnb →
About the role
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb is a mission-driven company dedicated to creating a world where anyone can belong anywhere. Our Community Support (CS) team is at the heart of that mission—delivering seamless, 10-star customer service experiences complemented by world-class, personalized human support that empowers hosts and guests at every step of their journey. As a Data Scientist working on Algorithms in CS, you will have the opportunity to collaborate with a strong team of engineers, product managers, designers and operation agents to enable personalized, fair and exceptional experience for guests & hosts using advanced LLM/ML modeling for Community Support. The Difference You Will Make: We're looking for a talented Data Scientist with LLM/ML expertise to join the Community Support Data Science team. In this role, you'll partner closely with the tech lead to tackle significant components of high-impact projects with a direct opportunity to shape and influence our AI-powered products, differentiated service experiences, and operational optimization strategies. The ideal candidate combines deep technical fluency in LLM/ML with a bias toward action and impact, comfort with ambiguity, and a passion for building scalable, scientific solutions. You’ll work on high-impact projects like: • Implement advanced techniques to automate the LLM evaluation process with high efficiency and quality. • Scale the high-quality synthetic datasets curation across various CS domains for training and evaluating LLM. • Build LLM/ML models to understand customer issues based on diverse datasets and identify failure modes and opportunities for improvement. • Build personalization models to offer differentiated experiences and maximize business impact. A Typical Day: • Discover Opportunities: Identify high-impact business opportunities through data exploration and model prototyping, and translate business problems into scientific formulations. • Uncover Insights: Analyze structured and unstructured data to uncover meaningful insights and craft actionable proposals that help shape strategy. • Build and Ship: Build and deploy production LLM/ML models that directly contribute to the launch of data-driven products, leveraging AI tools to enhance efficiency and impact. • Collaborate Cross-Functionally: Build strong relationships with cross-functional partners across Product, Design, Engineering, Operations, and Analytics to drive collaboration and innovation. • Influence Decisions: Communicate learnings to leaders and stakeholders in a clear, compelling manner that drives informed, data-driven decision-making. • Empowerment: Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision for how science drives platform outcomes. Your Expertise: • 2+ years of relevant industry experience (e.g. data/ML scientist, tech lead, junior faculty) and a Master’s degree or PhD in relevant fields. • State-of-the-art knowledge of AI/ML models. • Strong fluency in Python/R and SQL, observation causal inference skill is a plus. • Proven ability to communicate clearly and effectively to audiences of varying technical levels. • Ability to translate complex findings and results into compelling narratives that drive impact. • Excellent project management, communication, and collaboration skills. • A product-oriented mindset, wi