You will be:

• designing and developing statistical models for property price adjustments across time, location, quality, and condition,
• building spatial algorithms (adaptive heatmaps, geographic clustering, polygon-based property search) to capture local market dynamics,
• implementing comparable property recommendation with feature engineering across different property types,
• developing market analysis pipelines with solid diagnostics: trend fitting, outlier detection, goodness‑of‑fit metrics,
• integrating LLM‑based classification services for document and property analysis,
• exposing model outputs through production API endpoints and working with frontend engineers on data contracts,
• debugging models in production: edge cases, numerical issues, data quality problems.

Your profile:

• solid statistics background: regression, GAMs, mixed/random effects, link functions, robus...