# Senior Applied Scientist, Property Analytics at Figure AI

Figure AI is hiring a Senior Applied Scientist, Property Analytics. It pays $132k-$198k a year and Level rates it Builds AI ●●●●; you can [apply on Figure AI](https://jobsbylevel.com/go/ae74064c-dbcf-4e72-9379-dc4a8319a251?utm_medium=ai-agent).

AI Level 4, AI centrality 90 out of 100. Remote (Remote).

## Details

- Company: [Figure AI](https://jobsbylevel.com/companies/figure-ai)
- AI level: AI Level 4 (score 90 out of 100)
- Location: Remote (Remote)
- Salary: $132k-$198k
- Posted: November 12, 2026
- Apply: https://jobsbylevel.com/go/ae74064c-dbcf-4e72-9379-dc4a8319a251?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-applied-scientist-property-analytics-at-figure-ai-5400f3

## Prepare for this job

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## Description

About Figure Figure Technology Solutions, Inc. (Nasdaq: FIGR; OPEN: FGRS) is the leading blockchain-native capital marketplace for the origination, funding, sale and trading of tokenized assets. More than 480 partners use its loan origination system and capital marketplace. Collectively, Figure and its partners have originated over $30 billion of loans to date, among other products. The fastest growing components are Figure Connect, its credit marketplace, and Democratized Prime, Figure’s on-chain lend-borrow marketplace. Figure’s ecosystem also includes DART (Digital Asset Registry Technology) for asset custody and lien perfection, and $YLDS, a yield-bearing stablecoin registered with the SEC as a security under the Securities Act of 1933. Figure is the market leader in real-world asset (RWA) tokenization. The company has received triple-A ratings ratings from S&P and Moody’s on multiple loan securitizations, the first of its kind for blockchain finance. We’re proud to be recognized as one of Forbes’ Top 50 Fintech Companies and CNBC’s World’s Top Fintech Companies . About the Role We’re looking for a Senior Applied Scientist, Property Analytics to join our growing team! As Senior Applied Scientist, Property Analytics, you’ll help us reinvent real estate lending by tackling complex research and machine learning problems related to automated valuation models (AVMs), asset valuation, and process optimization. You’ll work alongside engineering, product, and business leaders on a team of 360-degree thinkers who combine advanced analytics and machine learning skills with deep domain knowledge, using some of the most fascinating data sets in the world. You’ll lead technical direction, mentor team members, and partner closely with MLOps engineers, Product Managers, Credit Risk Management, and Capital Markets subject matter experts to drive strategic initiatives from initial research to production deployment. What You’ll Do Lead the end-to-end design, architecture, development, and deployment of state-of-the-art automated valuation modeling (AVM) systems for novel lending products Architect and refine innovative machine learning, deep learning, and statistical models for asset valuation, incorporating spatial-temporal trends, macroeconomic factors, market liquidity, and property risk dynamics Establish robust quantitative frameworks for continuous model performance assessment, monitoring, and automated retraining across changing real estate cycles Build analytical tools and frameworks to empower cross-functional teams across risk, underwriting, and capital markets Partner closely with data infrastructure and MLOps engineering teams to drive initiatives that enhance data capabilities, build feature stores, and streamline real-time inference infrastructure Design useful data attributes and feature representations, leveraging structured, unstructured, and multimodal data sources (for example, property photos, listing descriptions, and spatial features) Perform exploratory data analysis, evaluate frontier AI capabilities, and make strategic recommendations to improve current decisioning frameworks and valuation accuracy Refactor and optimize existing analytical solutions and algorithmic components to improve scalability, reliability, and execution efficiency What We Look For Ph.D. or Master’s degree in a quantitative discipline (for example, Computer Science, Data Science, Statistics, Economics, Applied Mathematics, or Machine Learning) with 5+ years of industry experience (or 3+ years with a Ph.D.) building and deploying machine learning models in production Proven track record of developing statistical and machine learning models at an account, customer, or real estate asset level Solid understanding and hands-on application of advanced machine learning techniques, deep learning, spatial analytics, and AI capabilities Strong production-level programming skills in Python, SQL, and R Demonstrated experience in technical leadership,

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