Senior Applied Scientist, Property Analytics

Responsibilities

• Lead end-to-end design and deployment of automated valuation modeling systems
• Architect machine learning, deep learning and statistical models for asset valuation
• Establish quantitative frameworks for model performance monitoring and retraining
• Build analytical tools for risk, underwriting and capital markets teams
• Partner with MLOps teams on feature stores and real-time inference infrastructure
• Design features from structured, unstructured and multimodal data sources

Requirements

• PhD or Master's in a quantitative discipline with 5+ years building production ML models
• Track record developing statistical and machine learning models at asset level
• Hands-on advanced machine learning, deep learning and spatial analytics
• Production programming in Python, SQL and R
• Technical leadership and mentoring experience
• Strong communication with technical and executive stakeholders

Preferred Qualifications

• Experience with Automated Valuation Models or automated appraisal systems
• Survival analysis, econometric or spatial-temporal forecasting exposure
• Computer vision or NLP applied to real estate
• Spark, PyTorch or TensorFlow proficiency
• Monte Carlo, Bayesian inference or causal machine learning experience
• MLOps, AWS or GCP and model serving familiarity
• FRM or CFA progress or completion

About the Company

• Kiavi is a real estate lending company that uses data and technology to finance investors.