Real Estate Market Modeling: Build models applied to challenges such as valuation/pricing leveraging techniques from classic supervised ML to more advanced approaches.
Multimodal Embeddings: Create vector representations of Real Estate entities, such as listings, combining images, text, and structured attributes to power search, matching, deduping, or recommendations.
Data Analysis & Experimentation: Use SQL/Python to extract, clean, and analyze data; design experiments and evaluate model-product impact with robust metrics.
Model Operationalization: Ship models to production with capabilities such as monitoring, automated rollout, or CI/CD (in partnership with engineering).
Cross-functional Delivery: Partner with product, engineering, and operations teams to translate business problems into scalable ML solutions.
Qualifications
Proven Experience: 4–8 years in applied data science/ML,...
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