Senior / Lead AI Scientist (Personalisation & GenAI)

Role: Senior/Lead- 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.