Data Scientist, AirCover (Guest Travel Insurance)

Role Overview

Airbnb is seeking a Data Scientist to join the AirCover team, focusing on Guest Travel Insurance (GTI). In this role, you will work at the intersection of insurance, personalization, and machine learning, building intelligent systems to help guests discover the right coverage at the right moment. You will be part of a high-output Data Science team, collaborating daily with product, engineering, operations, and legal teams to deliver work that directly impacts guest trust and revenue.

The Difference You Will Make

We are looking for a machine learning expert passionate about owning hard problems end-to-end, from prototype to production. Your contributions and leadership will span across:

• Package personalization & ML-based recommendation: Evolve rule-based guest segmentation into a full ML recommendation system that surfaces the most relevant insurance options (e.g., trip cancellation, accidental damage coverage, on-trip protection) to each guest based on purchase intent, trip attributes, listing signals, and user history.
• Content personalization: Build models to rank and select benefit messaging for each guest, determining which coverages to highlight, their order, and framing, drawing on insights from segmentation experiments and LLM-assisted content prototyping.
• Intent modeling: Develop and productionize ML models (from gradient-boosted trees to deep learning) that predict a guest’s likelihood to value specific coverages, using structured booking data and unstructured signals.
• Journey understanding and optimization: Leverage reinforcement learning to personalize across the user journey, understanding user preferences on entry point, price, notification frequency, and trip characteristics.
• High-velocity experimentation: Design and run adaptive experiments to maximize learning within tight traffic constraints, strategically sequencing ERFs to advance the personalization roadmap.

A Typical Day

• Analyze experiment results to identify high-impact personalization opportunities and translate findings into clear scientific problem formulations that balance rigor with speed-to-learning.
• Collaborate closely with product managers, engineers, operations, legal, and privacy partners to align on ML requirements, de-risk design decisions, and gather requirements for explainability and compliance.
• Hands-on develop, evaluate, and ship ML models and data pipelines at scale—both batch and real-time, structured and unstructured—leveraging Airbnb’s paved-path tooling and an AI-native mindset.
• Rapidly prototype and iterate: transform new ideas into working models, gather early signals from experiments, and then productionize successful solutions.
• Present findings and proposals at team reviews and to technical, product, and executive stakeholders, making complex ML results understandable without oversimplification and building conviction for future roadmap.
• Stay current with research advancements; apply state-of-the-art developments in recommendation systems, LLMs, and personalization to elevate the team's output. Opportunity to publish externally or present at conferences.

Your Expertise

• 5+ years of relevant industry experience (e.g., ML scientist, tech lead, junior faculty) and a Master’s degree or PhD with 2+ years 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: able to articulate complex ML work clearly to engineers, product managers, legal, and executives, both in writing and verbally.
• Self-directed and passionate: thrives in a fast-moving environment, holds high standards, takes initiative, and finds satisfaction in shipping impactful solutions for guests.
• Product-oriented mindset: keeps the guest experience central to technical decisions and brings conceptual and innovative thinking to problem-solving. Publications or presentations in recognized venues are a plus.