Data Scientist

Property Finder is the leading property portal in the Middle East and North Africa (MENA) region, dedicated to shaping an inclusive future for real estate while spearheading the region’s growing tech ecosystem. At its core is a clear and powerful purpose: To change living for good in the region.

Founded on the value of great ambitions, Property Finder connects millions of property seekers with thousands of real estate professionals every day. The platform offers a seamless and enriching experience, empowering both buyers and renters to make informed decisions. Since its inception in 2007, Property Finder has evolved into a trusted partner for developers, brokers, and home seekers. As a lighthouse tech company, it continues to create an environment where people can thrive and contribute meaningfully to the transformation of real estate in MENA.

Position Summary

We are looking for a Data Scientist with hands-on experience in machine learning and statistical methods to help build predictive and optimization models across our property portal. You will work on models that improve pricing accuracy, lead scoring, and listing quality, from feature development through deployment, working closely with engineering and business teams to deliver measurable impact.

Key Responsibilities

• Design and implement predictive and optimization models using classical ML, statistical modeling, and deep learning techniques.
• Build and deploy models on AWS (SageMaker, Lambda, ECS), owning the full path from feature extraction to production, including MLOps practices like CI/CD for models and monitoring.
• Build evaluation pipelines and support A/B testing frameworks to validate model performance and reliability.
• Collaborate with engineering teams on production deployment, ensuring models meet latency and scalability requirements.
• Contribute to model monitoring practices, tracking performance drift and data quality over time.

Cross-Team Collaboration

• Partner with engineering to optimize model deployment and operational workflows.
• Work with Product, Strategy, and Commercial teams to align on project objectives and translate business goals into data-driven initiatives.

Desired Qualifications

Education

Bachelor's or above in Mathematics, Computer Science, Data Science, or a related quantitative field.

Experience

4+ years in Data Science or Analytics roles with a demonstrable track record of business impact.

Technical Skills

• Strong SQL and Python (pandas, NumPy, Scikit-learn), with experience in PyTorch or TensorFlow.
• Hands on experience with supervised and unsupervised methods, evaluation metrics, feature engineering, and model tuning.
• Experience deploying models on AWS, specifically SageMaker, Lambda, and ECS.
• Solid understanding of statistical methods, experimental design, and hypothesis testing.

Nice to Have

• Experience with model explainability (e.g. SHAP), as our models influence pricing and search outcomes.
• GenAI experience and prompt engineering.
• Computer vision or NLP background.

Soft Skills

• Strong communication skills, able to translate complex findings for non-technical audiences.
• Strong problem-solving ability, translating ambiguous business problems into technical solutions.

Why Join Us?

• Contribute to cutting-edge AI and ML projects in a dynamic and fast-paced environment.
• Collaborate with top talent across diverse teams and disciplines.
• Be part of an innovative culture that values advanced research, strategic thinking, and impactful execution.

Our promise to talent

At Property Finder, we believe talent thrives in an environment where you can be your best self. Where you are empowered to create, elevate, grow, and care. Our team is made up of the best and brightest, united by a shared ambition to change living for good in the region. We attract top talent who want to make an impact. We firmly believe that when our people grow, we all succeed.

Property Finder Guiding Principles

• Think Future First
• Data Beats Opinions, Speed Beats Perfection
• Optimise for Impact
• Act Like An Owner
• The Biggest Risk is Taking no Risk at All