Data Scientist

Overview

• 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.