Data Scientist | Corporate Services | Group Tech & Dig Platforms

Data Scientist | Corporate Services | Group Tech & Dig Platforms

Join to apply for the Data Scientist | Corporate Services | Group Tech & Dig Platforms role at Al-Futtaim Automotive

Job Requisition

Al-Futtaim Group is a diversified, privately held regional business headquartered in Dubai, United Arab Emirates. Structured into five operating divisions—automotive, financial services, real estate, retail and healthcare—Al-Futtaim employs more than 35,000 people across more than 20 countries. Our entrepreneurship and customer focus enable continued growth and innovation.

The Data Scientist role at Al‑Futtaim is centered on designing, building and product ionizing advanced analytics and GenAI‑powered solutions. The purpose of the role is to enhance insights, recommendations and decision‑making across enterprise platforms. Success is measured by the ability to develop scalable, reliable machine learning and GenAI models that meet enterprise standards of governance, security and compliance.

• Translate business problems into data science, statistical and machine learning solutions that drive measurable outcomes across enterprise use cases.
• Perform data exploration, feature engineering, model development and evaluation on large‑scale structured and semi‑structured datasets.
• Build and deploy predictive, prescriptive and descriptive models, ensuring interpretability, robustness and alignment with business objectives.
• Partner closely with business, product and analytics teams to validate assumptions, define success metrics and deliver actionable insights.
• Apply GenAI techniques to augment data science workflows, including LLM‑based insight generation, summarization, classification and decision support.
• Design and implement Retrieval‑Augmented Generation (RAG) solutions to ground LLM outputs in enterprise data and analytical results.
• Collaborate on GenAI‑enabled analytical applications with a focus on accuracy, relevance and explainability.
• Evaluate and benchmark GenAI outputs using quantitative and qualitative metrics, ensuring alignment with business and analytical standards.
• Productionize data science and GenAI models using enterprise‑grade MLOps / LLMOps practices, including versioning, deployment, monitoring and retraining strategies.
• Build scalable, secure and reliable analytical pipelines in collaboration with Data Engineering and Cloud teams.
• Monitor model performance, data drift and GenAI output quality, and drive continuous improvements based on real‑world usage.
• Ensure solutions meet enterprise requirements for governance, security, compliance and responsible AI.
• Define and track model and GenAI performance metrics (accuracy, stability, bias, latency, business impact).
• Run experiments and controlled rollouts to optimize models, GenAI prompts and retrieval strategies.
• Continuously enhance solutions through feedback loops, experimentation and evolving.

• Strong foundation in statistics, machine learning, and applied data science.
• Proficiency in Python, SQL, and Spark with expertise in data processing and analytical pipelines.
• Hands‑on experience with the Databricks ecosystem for deploying data science and GenAI solutions.
• Practical exposure to MLOps / LLMOps practices, including model versioning and monitoring.

This role reports to the Data Science Lead.

• 8+ years of experience in Data Science / AI Engineering, focusing on building and deploying machine learning models, including supervised, unsupervised and time‑series models.
• 6+ years of experience in feature engineering, model evaluation and performance optimization.
• 4+ years of experience with NLP or language‑based systems, including text classification, information extraction and semantic modeling.
• 2+ years of experience in delivering GenAI or conversational AI solutions in production, focusing on applied LLM use cases, RAG and enterprise deployment.

Mid‑Senior level

Full‑time

Engineering and Information Technology