Data Scientist

Huspy; United Arab Emirates; On-site; GBP 50,000 - 85,000; Full time

Job summary

Huspy, a leading property technology company in the UK, is seeking a Data Scientist with 4–8 years of experience in ML. The successful candidate will drive real estate market modeling, use SQL and Python for data analysis, and operationalize models in production. Strong communication skills and a Bachelor’s in STEM are required. This is an exciting opportunity to join a fast-growing company transforming the homebuying journey with innovative technology.

Qualifications

• 4–8 years in applied data science/ML with real-world KPI impacts.
• Mastery of SQL and Python frameworks for data handling.
• Experience with MLOps practices and model deployment.

Responsibilities

• Build models for real estate market challenges using ML techniques.
• Create vector representations of real estate entities for enhanced services.
• Analyze data using SQL/Python and evaluate model-product impact.

Skills

Data modeling

SQL

Python

Machine Learning

Data analysis

Communication skills

Education

Bachelor’s in STEM

Master's in relevant field

Tools

Pandas

NumPy

Scikit-learn

Job description

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.