Data Science Lead
Lead data science strategy and architecture for scalable analytics and ML systems. Design data architectures, evaluate novel data sources, establish analytical methodologies, and bridge R&D to production.
Senior Data Scientist, Guest Travel Insurance (Algorithms)
Senior Data Scientist building ML-driven personalization and recommendation systems for Guest Travel Insurance at Airbnb, focusing on coverage recommendations, intent modeling, and high-velocity experimentation.
179k – 210kUnited StatesData ScienceRemote5+ YOE
About the role
Responsibilities
- Evolve rule-based guest segmentation into ML recommendation systems for insurance coverage personalization based on purchase intent, trip attributes, listing signals, and user history.
- Build models to rank and select benefit messaging for each guest, determining which coverages to highlight, order, and framing using segmentation experiments and LLM-assisted content prototyping.
- Develop and productionize ML models (gradient-boosted trees to deep learning) that predict guest likelihood to value specific coverages using structured booking data and unstructured signals.
- Leverage reinforcement learning to personalize across user journeys, optimizing entry points, pricing, notification frequency, and trip characteristics.
- Design and run adaptive experiments to maximize learning within traffic constraints and sequence ERFs for the personalization roadmap.
Requirements
- 5+ years of relevant industry experience 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, including feature engineering, user modeling, and the full ML lifecycle.
- Strong fluency in Python and SQL; experience with TensorFlow or PyTorch, Airflow, and data warehouse environments.
- Deep understanding of ML algorithms (gradient-boosted trees, deep learning, optimization) and experiment design, including A/B testing and multi-armed bandits.
- Exceptional communication skills for explaining complex ML work to engineers, product managers, legal, and executives.
Nice-to-Haves
- Experience with LLMs, Computer Vision, or content-understanding topics.
- Causal inference skills.
- Publications or presentations in recognized venues.
Skills
PythonSQLTensorFlowPyTorchAirflowGradient Boosted TreesDeep LearningA/B TestingMulti-Armed BanditsReinforcement LearningFeature EngineeringRecommendation Systems
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