Airbnb

Product Manager for Airbnb's Relevance and Personalization team, focusing on AI systems that connect guests to listings and personalize the travel experience. The role involves setting strategy, driving roadmap execution, and partnering with ML engineers and researchers to ship products at global scale.

Staff Data Scientist at Airbnb focused on Guest & Host marketplace optimization, ranking, and AI-powered search experiences. The role involves building and shipping customer-facing features, developing causal inference models, and creating scalable data products for ranking and personalization. It requires expertise in machine learning, causal inference, and collaboration with ML Engineers and Product teams to launch and evaluate AI-driven improvements.

Product Manager role focused on shipping AI-powered features for guest-facing quality merchandising on Airbnb. This involves defining requirements for generative AI and ML ranking systems, partnering with Data Science to evaluate model performance, and ensuring trust and quality in the marketplace. The role requires a strong understanding of AI/ML outputs and translating them into product decisions, with a focus on consumer products and global scale.

Senior Staff Machine Learning Engineer at Airbnb focused on Communication & Connectivity, architecting and implementing advanced ML solutions including recommendation engines, ranking systems, intent detection models, and LLM integrations for customer-facing products. The role involves shaping ideas from inception to production and leading ML, Data, and Product engineers.

Manager for Fraud Intelligence at Airbnb, focusing on leading defenses against novel fraud and abuse, shaping proactive strategies, and building systemic defenses to reduce fraud loss and enhance platform trust. The role involves analyzing fraud signals, developing data-informed decisions, and collaborating cross-functionally to implement countermeasures.

Senior Manager, Advanced Analytics, Fraud & Safety Operations at Airbnb. Leads a team of analysts to turn safety measurement into governed, self-serve decision systems for various departments. Focuses on building systems for fraud, safety, and quality, including scenario simulators and data democratization, to enable data-driven decisions. Requires experience in analytics, risk, or safety, team leadership, and ownership of large-scale data products in regulated environments. Familiarity with ML pipelines and understanding of incident impact analysis is needed.