Lead Data Scientist

Role overview Lead the development and delivery of predictive analytics for property operations, from framing business questions through deploying models and measuring their impact. The role combines hands-on data science with technical leadership, partnering with product, revenue, data, AI, and engineering teams to turn large-scale telemetry into useful, reliable capabilities.

Responsibilities - Work with product and revenue partners to define modeling problems, intended outcomes, and success measures. - Explore data and create visualizations that clarify patterns and inform model design. - Build models for time-series telemetry, including anomaly detection, failure prediction, and time-to-event analysis. - Develop reusable, documented code and set modeling and documentation practices for a growing team. - Deploy models in Databricks and maintain their quality through monitoring, drift diagnosis, and retraining. - Partner with engineering to scale production workloads and design experiments that connect model performance to customer or revenue outcomes.

Requirements - A quantitative bachelor's degree or equivalent professional experience. - At least seven years in data science, including production models relied on by customers or products. - Deep experience with time series, anomaly detection, and ensemble methods. - Practical experience modeling data in Databricks, including capabilities such as feature stores and experiment management. - Advanced SQL and Python skills for working with complex datasets. - Strong experiment design and causal or impact measurement skills, with the ability to explain technical ideas to nontechnical audiences.

Nice to have Experience applying large language models in data science workflows, enabling self-service analytics in Databricks, or building end-to-end machine-learning pipelines with MLOps practices. Background in property technology, real estate, IoT, or SaaS, and familiarity with Git and Terraform, are also useful.

Benefits and work setup The listing describes medical, dental, vision, and life insurance, paid time off, retirement contributions, paid parental leave, and other insurance and employee stock purchase options for US employees.