Data Scientist

• Build models for real estate market challenges using ML techniques.
• Create multimodal embeddings for property listings.
• Design and evaluate experiments to measure model impacts.

Conocimientos

SQL Python Applied Data Science Machine Learning Data Analysis

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 in Málaga, Spain, is seeking an experienced Data Scientist to drive and build solutions using machine learning in real estate. The ideal candidate will have 4-8 years of experience, strong skills in SQL and Python, and a solid understanding of MLOps principles. You'll work cross-functionally with product and engineering teams to solve complex business problems.

Responsibilities include market modeling, data analysis, and operationalizing models. Strong communication and ownership skills are essential for success in this role., * 4-8 years in applied data science/ML, delivering models impacting real-world KPIs.

• Strong command of SQL and Python, especially in data processing frameworks.
• Experience with MLOps, model deployment, CI/CD processes., * 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).