Role: Senior AI/ML Scientist – Personalization & GenAI (Dubai based) Join a high-performing Data Science team whose mission is to drive competitive value through scalable AI solutions. The team builds models that enhance user experiences, enable better decision-making, improve operational efficiency, and shape the regional AI ecosystem. As a senior technical leader, you’ll help define the future of personalization and user engagement using Generative AI and advanced machine learning. Key Responsibilities Lead end-to-end AI transformation focused on personalization in a consumer-facing application. Define and execute a long-term vision for customer acquisition and engagement strategies powered by data and AI. Conduct exploratory analysis to understand user behavior, discover optimization opportunities, and develop behavior models to inform product enhancements. Design and deploy data/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product features. Stay up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7 years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A/B testing methodologies, and experiment design. Solid background in ranking, recommendation, and retrieval systems. Familiarity with large-scale data tools (Hadoop, BigQuery, Amazon EMR, etc.). Experience with BI tools and visualization platforms such as Tableau, Qlik, or MicroStrategy. Bonus: Experience with geospatial data and advanced analytics platforms.