Data Scientist

Huspy; Madrid; Presencial; EUR 40.000 - 70.000; Jornada completa

Descripción de la vacante

Huspy, based in Madrid, is seeking a Data Scientist with 4–8 years of experience in applied data science and machine learning. The role involves building real estate market models, analyzing data using SQL and Python, and deploying models. Ideal candidates will have expertise in data manipulation and communication with diverse stakeholders. This position offers a unique opportunity to impact the rapidly evolving real estate sector with advanced technology and analytics.

Formación

• 4–8 years in applied data science/ML with real-world KPIs.
• Proficiency in SQL and Python for data manipulation.
• Experience with MLOps including model deployment and maintenance.

Responsabilidades

• Build models for real estate market challenges like pricing.
• Create vector representations for real estate entities.
• Analyze data using SQL/Python to inform model impact.

Conocimientos

Applied data science/ML experience

SQL

Python

MLOps fundamentals

Communication with stakeholders

Educación

Bachelor’s in STEM

Master’s in STEM (nice to have)

Herramientas

Pandas

NumPy

Scikit-learn

Descripción del empleo

The Story So Far: We’re Building a Global Brand in Real Estate

Huspy is one of the leading property technology companies in EMEA. Launched in 2020, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by 2026. Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we’ve entered. We’ve raised over $140 million (Series A and Series B) from the world’s top investors, including Sequoia Capital, Founders Fund and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools. We’ve built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting‑edge technology to one of the world’s most traditional industries. We’re transforming how property transactions happen — faster, smarter, and better for everyone. We’re not slowing down. The question is: will you be part of what’s next?

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 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.
• 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).

By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.