Senior Data Scientist, Guest Travel Insurance – Algorithms
Job Description:
• Dig into experiment results to surface high-impact personalization opportunities; translate what you find into crisp scientific problem formulations that balance rigor with speed-to-learning.
• Work closely with product managers, engineers, operations, legal, and privacy partners to align on ML requirements, de-risk design decisions, and gather requirements on explainability and compliance.
• Hands-on develop, evaluate, and ship ML models and data pipelines at scale—batch and real-time, structured and unstructured—using Airbnb’s paved-path tooling and AI native mindset
• Prototype and iterate quickly: turn a new idea into a working model in a prototype, get early signals from an experiment, then productionize what works. You move fast and don’t wait to be asked.
• Present findings and proposals at team reviews and to technical, product, and executive stakeholders—making complex ML results legible without dumbing them down, and generating conviction on the roadmap ahead.
• Stay current with the research community; draw on state-of-the-art advances in recommendation systems, LLMs, and personalization to raise the bar for what the team ships. Occasionally publish externally or present at conferences to advance Airbnb’s scientific standing.
Requirements:
• 5+ years of relevant industry experience (e.g., ML scientist, tech lead, junior faculty) and a Master’s degree or PhD with 2+ yrs in a relevant field.
• Proven hands-on experience building and shipping personalization and recommendation systems at scale: strong intuition for feature engineering, user modeling, and the full ML lifecycle (training, serving, monitoring, iteration). Experience with LLMs, Computer Vision or content-understanding topics is a strong plus.
• Strong fluency in Python and SQL; hands-on experience with TensorFlow or PyTorch, Airflow, and a data warehouse environment.
• Deep understanding of ML algorithms (gradient-boosted trees, deep learning, optimization) and experiment design—including A/B testing, multi-armed bandits, and the practical constraints of running experiments at scale. Causal inference skills are a plus.
• Exceptional communicator: you can make complex ML work legible to engineers, product managers, legal, and executives alike— written and verbal. You treat communication as a core part of the job, not an afterthought.
• Self-directed and passionate: you’re energized by a fast-moving environment where there are always more good ideas than time; you hold yourself to a high standard without being asked, take initiative to unblock yourself, and find genuine satisfaction in shipping things that matter to guests.
• Product-oriented mindset: you keep the guest experience at the center of technical decisions and bring conceptual and innovative thinking to how you frame and solve problems. Publications or presentations in recognized venues are a plus.
Benefits:
• Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
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• Dig into experiment results to surface high-impact personalization opportunities; translate what you find into crisp scientific problem formulations that balance rigor with speed-to-learning.
• Work closely with product managers, engineers, operations, legal, and privacy partners to align on ML requirements, de-risk design decisions, and gather requirements on explainability and compliance.
• Hands-on develop, evaluate, and ship ML models and data pipelines at scale—batch and real-time, structured and unstructured—using Airbnb’s paved-path tooling and AI native mindset
• Prototype and iterate quickly: turn a new idea into a working model in a prototype, get early signals from an experiment, then productionize what works. You move fast and don’t wait to be asked.
• Present findings and proposals at team reviews and to technical, product, and executive stakeholders—making complex ML results legible without dumbing them down, and generating conviction on the roadmap ahead.
• Stay current with the research community; draw on state-of-the-art advances in recommendation systems, LLMs, and personalization to raise the bar for what the team ships. Occasionally publish externally or present at conferences to advance Airbnb’s scientific standing.
Requirements:
• 5+ years of relevant industry experience (e.g., ML scientist, tech lead, junior faculty) and a Master’s degree or PhD with 2+ yrs in a relevant field.
• Proven hands-on experience building and shipping personalization and recommendation systems at scale: strong intuition for feature engineering, user modeling, and the full ML lifecycle (training, serving, monitoring, iteration). Experience with LLMs, Computer Vision or content-understanding topics is a strong plus.
• Strong fluency in Python and SQL; hands-on experience with TensorFlow or PyTorch, Airflow, and a data warehouse environment.
• Deep understanding of ML algorithms (gradient-boosted trees, deep learning, optimization) and experiment design—including A/B testing, multi-armed bandits, and the practical constraints of running experiments at scale. Causal inference skills are a plus.
• Exceptional communicator: you can make complex ML work legible to engineers, product managers, legal, and executives alike— written and verbal. You treat communication as a core part of the job, not an afterthought.
• Self-directed and passionate: you’re energized by a fast-moving environment where there are always more good ideas than time; you hold yourself to a high standard without being asked, take initiative to unblock yourself, and find genuine satisfaction in shipping things that matter to guests.
• Product-oriented mindset: you keep the guest experience at the center of technical decisions and bring conceptual and innovative thinking to how you frame and solve problems. Publications or presentations in recognized venues are a plus.
Benefits:
• Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
Apply tot his job
Apply To this Job