Data Scientist

• Build real estate market models for valuation and pricing.
• Create vector representations of real estate entities.
• Analyze data and design experiments to evaluate model impact.

Conocimientos

Data Science Machine Learning SQL Python Communication

Educación

Bachelor's in STEM Master's in STEM

Herramientas

Pandas NumPy Scikit-learn Descripción del empleo The Main Event: What You'll Drive, Build, and Own

• 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.

Huspy, located in Marbella, Spain, is seeking a Data Scientist to drive real estate market modeling and create multimodal embeddings. The role requires proven experience in data science and machine learning, focusing on deploying robust models.

The ideal candidate has advanced SQL and Python skills, with a good understanding of MLOps. An academic background in STEM is preferred. The position emphasizes cross-functional collaboration and effective communication with stakeholders., * 4-8 years in applied data science/machine learning delivering impactful models.

• Proficiency in SQL and Python for building reliable data pipelines.
• Experience with MLOps fundamentals for model deployment and maintenance., * 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.
• MLOps Fundamentals: Experience deploying/maintaining models (batch or real-time), versioning, CI/CD basics, observability, and reproducible training.
• Communication & Ownership: Clear with technical/non-technical stakeholders; can scope, prioritize, and explain tradeoffs.
• Comfortable with uncertainty, data quality issues, leakage risks, and market dynamics (location, seasonality, inventory shifts).
• Nice to Have: Software engineering experience; multimodal/vision experience; voice AI (ASR/NLU) exposure.
• Academic Background: Bachelor's in STEM (Master's a plus).