Senior 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.

We are seeking an accomplished Senior Data Scientist with deep expertise in Generative AI
, and solid foundations in ML Engineering to join our forward-thinking AI & Data Science team. You will play a pivotal role in leading cutting-edge AI initiatives, scaling data-driven strategies, and shaping the future of AI at Property Finder.

This senior role requires strong technical and research depth, a collaborative mindset, and a proven ability to translate business challenges into impactful AI solutions. You will also act as a mentor to junior scientists and influence strategic decision-making across the company.

• Lead the design and implementation of complex predictive and optimization models using classical ML/statistical methods, deep learning architectures, and generative techniques.

• Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such as enhanced personalization, lead qualification, content generation, and workflow automation.

• Own the end-to-end ML lifecycle
  : from hypothesis generation, experimentation, evaluation, and explainability, to scalable deployment in production systems.

• Develop and enforce rigorous evaluation and monitoring pipelines
  , including A/B testing, drift detection, and model fairness/robustness.

• Guide the development of advanced analytics and visualization solutions to support strategic business decisions at scale.

• Collaborate closely with engineering teams to ensure resilient, low-latency, and production-grade deployment of AI systems.

• Embed trust, transparency, and auditability in all models—ensuring alignment with ethical AI and governance frameworks.

• Stay abreast of the latest in AI research and industry trends to keep our technology stack at the forefront.

• Implement MLOps and deployment best practices (CI/CD, automated workflows, model registry, versioning, and lifecycle management).

• Act as a technical leader and mentor for junior team members, fostering a culture of excellence, innovation, and continuous learning.
• Collaborate with Data Platform and Engineering teams to optimize model deployment pipelines and infrastructure.
• Partner with Product, Strategy, Commercial, and Executive stakeholders to define AI roadmaps, align on business priorities, and communicate insights effectively.

• Education
  :
  Master’s or PhD in Computer Science, Machine Learning, Data Science, or a related field.
• Experience
  :{

  • 5+ years of experience in applied data science or machine learning engineering roles.

  • Proven track record of deploying models in production environments with measurable business impact.

  • Experience guiding junior data scientists or leading end-to-end ML projects independently.

  }
• Technical Skills
  :{

  • Expertise in supervised/unsupervised learning, deep learning (CNNs, RNNs, transformers), and statistical modeling.

  • Strong foundation in scenario modeling, optimization, and evaluation metrics for performance and fairness.

  • Proficiency in Python (pandas, Num Py, scikit-learn) and deep learning libraries (PyTorch or Tensor Flow).

  • Hands‑on experience with LLMs, prompt engineering, fine‑tuning, and retrieval‑augmented generation (RAG) pipelines.

  • Experience integrating ML models via APIs and embedding AI in enterprise systems.

  • Deep…