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# Data Scientist

- **Company:** Huspy
- **Location:** Marbella, Spain
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Continuous Integration, Python (Programming Language), Machine Learning, NumPy, Software Engineering, SQL Databases, Management of Software Versions, Core Voice Platform, Pandas, Scikit Learn, Machine Learning Operations, Natural Language Understanding, Data Pipelines
- **Published:** July 27, 2026
- **Apply:** https://www.buscojobs.com.es/data-scientist-en-marbella-ID-364559753

## About the Role

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.
xcskxlj
Academic Background: Bachelor's in STEM (Master's a plus).
#J-*****-Ljbffr

## Description

The Main Event: What You'll Drive, Build, and Own¿Todo listo para enviar su solicitud?Asegúrese de comprender todas las responsabilidades y tareas asociadas a este puesto antes de continuar.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 Perfect Match: What It Takes to Succeed at HuspyProven 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.xcskxljAcademic Background: Bachelor's in STEM (Master's a plus).#J-*****-Ljbffr


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