Data Scientist

Huspy in Alicante, Spain, seeks a Data Scientist to build and operationalize models for the Real Estate market. You will collaborate with cross-functional teams to tackle complex business problems using machine learning., 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.

The ideal candidate has 4-8 years of experience in data science, proficiency in SQL and Python, and a Bachelor’s in a STEM field. Strong communication skills are essential for effective stakeholder engagement., * 4-8 years in applied data science/ML, delivering models that move real-world KPIs.

• Strong in SQL/Python frameworks such as Pandas/NumPy/Scikit-learn.
• Experience in deploying/maintaining ML models with CI/CD basics., * Build models for Real Estate market challenges using ML techniques.
• Create multimodal embeddings for Real Estate entities.
• Design experiments and analyze data using SQL/Python.

Conocimientos

Data analysis Machine Learning SQL Python Model Operationalization Communication

Educación

Bachelor’s in STEM Master’s in STEM, * 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).