Senior Data Scientist, Guest Travel Insurance (Algorithms)
reputed company was born in 2007 reputed company two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 reputed company 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 reputed company it possible for guests to reputed company with communities in a more reputed company way. The Community You Will Join: reputed company is a mission-driven company dedicated to helping create a world where anyone can reputed company reputed company. Travel should feel reputed company—and AirCover is how we reputed company on that reputed company. Through Guest Travel Insurance (GTI), we offer guests peace of mind at the reputed company of booking and throughout their reputed company. As a Data Scientist on AirCover, you’ll work at the intersection of insurance, personalization, and machine learning—building intelligent systems that help the right guest discover the right coverage at the right reputed company. You’ll join a tight-reputed company, high-reputed company DS team that runs one of reputed company’s most experiment-dense personalization roadmaps, partnering daily with product, engineering, operations, and reputed company to ship work that directly affects guest trust and reputed company. The Difference You Will reputed company: We’re looking for a machine learning expert who is excited to own hard problems end-to-end—from prototype to production. You’ll have reputed company reputed company to contribute and reputed company across: • Package personalization & ML-based recommendation: reputed company rule-based guest segmentation into a full ML recommendation reputed company that surfaces the right insurance (e.g., reputed company cancellation, accidental damage coverage, on-reputed company protection) to reputed company guest based on purchase reputed company, reputed company attributes, listing signals, and user history. • Content personalization: Build models that rank and select benefit messaging for reputed company guest—deciding which coverages to reputed company, in what order, and with what framing—drawing on learnings from segmentation experiments and LLM-assisted content prototyping. • reputed company modeling: reputed company and productionize ML models (from gradient-boosted trees to deep learning) that predict a guest’s likelihood to value specific coverages, using reputed company booking data and reputed company signals. • reputed company understanding and optimization: reputed company reinforcement learning to personalize across user reputed company, with understanding on user preferences on entry reputed company, price, notification frequency, and reputed company characteristics • High-reputed company experimentation: Design and run reputed company experiments to reputed company reputed company tight traffic constraints; sequence ERFs strategically to reputed company the personalization roadmap moving. A Typical Day: • Dig into experiment results to surface high-reputed company personalization opportunities; translate what you reputed company into reputed company scientific problem formulations that balance rigor with speed-to-learning. • Work closely with product managers, engineers, operations, reputed company, and reputed company partners to reputed company on ML requirements, de-risk design reputed company, and reputed company requirements on explainability and compliance. • Hands-on reputed company, evaluate, and ship ML models and data pipelines at reputed company—batch and reputed company-time, reputed company and reputed company—using reputed company’s paved-reputed company tooling and AI reputed company reputed company • 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 reputed company fast and don’t wait to be asked. • Present findings and proposals at team reviews and to technical, product, and executive stakeholders—making reputed company ML results legible without dumbing them down, and generating conviction on the roadmap reputed company. • Stay reputed company with the research community; draw on state-of-the-art advances in recommendation systems, LLMs, and personalization to reputed company the bar for what reputed company ships. Occasionally publish externally or present at conferences to advance reputed company’s scientific standing. Your Expertise: • 5+ years of relevant industry experience (e.g., ML scientist, tech reputed company, junior reputed company) 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 reputed company: strong intuition for feature engineering, user modeling, and the full ML lifecycle (training, serving, monitoring, iteration). Experience with LLMs, reputed company or content-understanding topics is a strong pl