It Analyst jobs in United Arab Emirates

Job summary

A leading real estate technology firm in Dubai is seeking an experienced Data Scientist to join their AI & Data Science team. The ideal candidate will possess skills in Machine Learning Engineering and Generative AI, with at least 3 years of experience. This role involves designing predictive models, optimizing AI systems, and collaborating with cross-functional teams. Come be part of an innovative culture that values advanced research and impactful execution.

Benefits

Qualifications

• Bachelor or above in Computer Science, Data Science, Machine Learning, or a related field.
• At least 3+ years in Data Science or MLE roles and foundational MLOps practices.
• Working knowledge of advanced predictive modeling, optimization, scenario analysis, and statistical methodologies.
• Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning.
• Proficiency in Python (pandas, NumPy, Scikit-learn); experience with PyTorch or TensorFlow for deep learning.
• Experience with API development and connecting AI systems to external platforms.
• Hands-on experience in applied GenAI/LLMs/Agentic AI augmented with knowledge of transformer-based architectures, prompt engineering, fine-tuning, and retrieval-augmented systems.
• Experience in leveraging cloud platforms (AWS, GCP, Azure) for scalable AI solutions.
• Foundational understanding of ML pipelines and Hands-on experience in deployment processes, version control systems (e.g., Git), CI/CD workflows, and containerization tools like Docker.
• Effective communication and collaboration skills, particularly in cross-functional environments.
• Strategic mindset with the ability to translate business goals into data-driven initiatives.

Responsibilities

• Design and implement advanced predictive and optimization models.
• Drive applied innovation in Large Language Models (LLMs), Generative AI, and Agentic AI systems.
• Build end-to-end model development, including experimentation, rigorous evaluation, and deployment.
• Build and maintain robust evaluation pipelines and A/B testing frameworks.
• Collaborate with engineering teams for production-grade scalability.
• Integrate trust and explainability into model design.
• Continuously optimize model performance for scalability and efficiency.
• Implement MLOps and deployment best practices.