Develop and maintain product-focused data science and machine learning models for land-use suitability, land valuation, comparable transactions, and community sentiment. Source and curate geospatial and market datasets, design evaluation frameworks, improve existing models, and collaborate with design, product, and engineering to deliver customer-facing insights. The role requires production-quality Python, SQL, geospatial tooling, reproducible workflows, and the ability to explain analytical outputs to non-experts.

Lead development and operations of geospatial data pipelines and lakehouse systems. Migrate orchestration to Prefect, extend sources and transforms, optimize Postgres and Iceberg stores, build observability and AI-agent readiness, and integrate cross-team tooling with product and ML teams.

Lead Aarden's publishable research: define research agenda, mine proprietary parcel and infrastructure data, run analyses using ML/AI tools, validate methodology with the data team, and publish insights (LinkedIn posts, white papers, media) that serve land-focused clients.