UAE national_Data Science Manager | Group Technology | Corporate Services

UAE national_Data Science Manager | Group Technology | Corporate Services

Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United Arab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organisation to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.

By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day.

Overview of the role:

As the Data Science Manager, you will play a critical role in designing, developing, and deploying next-generation AI systems across various domains. This includes working with large language models (LLMs), Co-pilot, agentic AI, and other advanced AI applications. You will leverage a variety of cutting-edge techniques, such as semantic learning, reinforcement learning, deep learning, natural language processing (NLP), computer vision, and multi-modal learning to build intelligent, scalable, and adaptive AI-driven solutions.
Your expertise will extend beyond conversational agents to areas like autonomous decision-making systems, personalized recommendation engines, predictive analytics, and advanced automation. As part of the team, you'll contribute to creating highly dynamic, context-aware, and adaptive AI systems that interact seamlessly with users, devices, and external platforms.

What you will do:

• Innovative AI Development: Design, develop, and deploy cutting-edge AI systems, including large language models (LLMs), Co-pilot, agentic AI, and other advanced AI-driven applications.
• Diverse AI Techniques: Utilize a wide range of AI methodologies such as semantic learning, reinforcement learning, deep learning, natural language processing (NLP), computer vision, and multi-modal learning.
• AI System Scalability & Performance: Build scalable, efficient, and adaptive AI models capable of handling diverse use cases across different lines of business and platforms.
• Beyond Chatbots: Work on applications beyond conversational agents, including autonomous decision-making systems, personalized recommendation engines, predictive analytics, and advanced automation.
• AI-Powered Interactions: Focus on creating dynamic, context-aware, and personalized AI systems that enhance user interaction with virtual assistants, autonomous agents, and AI-powered co-pilots.
• Continuous Research & Innovation: Stay at the forefront of AI research and trends, implementing the latest AI techniques and continuously optimizing models to improve performance and functionality.
• Collaborative Development: Collaborate with cross-functional teams to develop and deploy solutions that integrate AI into complex, real-world environments, ensuring high levels of user satisfaction and impact.
• End-to-End Solution Design: Take responsibility for the end-to-end lifecycle of AI solutions, from research and development to deployment and maintenance.
  

Required Skills to be successful:

• UAE national
• 10+ years of experience in Data Science

What equips you for the role:

• A Master's degree in Statistics, Data Science, Machine Learning, Mathematics, Computer Science, or a related quantitative field.
• 10+ years of experience in Data Science, with at least 4+ years focused on developing and deploying Gen AI based solutions.
• Deep Learning & Neural Networks: Strong experience in deep learning frameworks like TensorFlow, PyTorch, Keras, and MXNet for building, training, and deploying neural networks.
• Natural Language Processing (NLP): Expertise in NLP techniques, including tokenization, named entity recognition (NER), sentiment analysis, topic modeling, and sequence-to-sequence models (e.g., transformers, BERT, GPT).
• Large Language Models (LLMs): Proficiency in working with LLMs such as GPT-3, GPT-4, T5, BERT, or custom transformer-based models for building conversational AI, co-pilots, and agentic systems.
• Vector Databases & Embedding Models: Hands-on experience with vectorizing data and working with vector databases (e.g. Pinecone, Faiss, Milvus, Weaviate) to enable similarity search, efficient retrieval, and semantic search across large datasets.
• Semantic Learning & Representation Learning: Knowledge of semantic learning techniques and representation learning methods for improving model understanding, reducing bias, and enhancing contextual accuracy.
• Multi-Modal AI: Experience in multi-modal learning, combining various data types (e.g., text, audio, video) to develop intelligent systems capable of handling complex, diverse inputs.
• Machine Learning Frameworks & Tools: Proficient in ML libraries like Scikit-learn, XGBoost, LightGBM, and other tools for model training, optimization, and evaluation.
• Cloud Computing & AI Infrastructure: Experience with cloud platforms (AWS, Google Cloud, Azure) and deploying AI models in cloud environments using Kubernetes, Docker, or serverless architectures.
• API Development & Integration: Familiarity with developing RESTful APIs for integrating AI models into production systems and working with API frameworks (Flask, FastAPI).
• Version Control & Collaboration Tools: Proficient with Git, GitHub, or GitLab for version control and collaborative development in a team-oriented environment.
• MLOps & Continuous Integration: Knowledge of MLOps practices for managing the AI lifecycle, including model versioning, CI/CD pipelines, and automation tools (e.g., Jenkins, MLflow).