Real Estate Market Modeling: 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).
The Perfect Match: What It Takes to Succeed at Huspy
Proven Experience: 4–8 years in applied data science/ML, delivering models that move real-world KPIs.
SQL & Python Mastery: Strong in frameworks such as Pandas/NumPy/Scikit-learn...building reliable data pipelines, model training and evaluation.
Experience deploying/maintaining models (batch or real-time), versioning, CI/CD basics, observability, and reproducible training.
Comfortable with uncertainty, data quality issues, leakage risks, and market dynamics (location, seasonality, inventory shifts).
Nice to Have: Software engineering experience; Academic Background: Bachelor’s in STEM (Master’s a plus).

📌 Data scientist (España)
🏢 HUSPY
📍 España