Senior Data Scientist

Headquartered in Abu Dhabi, United Arab Emirates, specializes in developing AI-driven intelligent systems for defense and industrial sectors by integrating engineering and supply chain intelligence. The company focuses on transforming unstructured data—such as military standards and regulatory texts—into actionable insights through advanced AI models like generative AI, NLP, and predictive analytics, ensuring accuracy and reliability. Their solutions support high-stakes decision making, compliance automation, and risk forecasting to bolster critical operations and secure supply chain resilience.

We are seeking a Senior Data Scientist to lead the technical development and deployment of high-impact AI initiatives for advanced defense capabilities. In this pivotal role, you will transition from exploratory modeling to building production-grade AI systems that directly enhance the design, manufacturing, and procurement processes. You will serve as the technical liaison between unstructured data sources—such as regulatory texts and technical documentation—and structured engineering systems, including BIM/IFC models and SAP S/4

HANA. Working within a structured delivery framework from Sprint Zero to Stage Gate, you will design and deploy AI engines that power two critical programs: the platform, which accelerates the systems engineering lifecycle, and Intelligent Supply Chain, which delivers predictive spend and risk analytics. Your expertise will drive innovation at the intersection of generative AI, predictive modeling, and system integration, ensuring compliance, efficiency, and resilience in high-stakes defense applications.

• Lead the development and deployment of generative AI and NLP solutions for engineering applications within the platform, including data exploration and analysis of large domain-specific datasets from both structured and unstructured sources to identify patterns and ensure data quality standards are met.
• Design, fine-tune, and deploy Large Language Models (LLMs) to interpret complex regulatory texts such as building codes and military standards, extracting structured rules for automated compliance checking and validation.
• Convert interpreted regulatory content into computer-processable formats (e.g., object-property-condition-value tuples) to enable execution by downstream compliance engines and systems.
• Architect NLP-driven methods to map natural language requirements directly to metadata entities across various schemas (e.g., linking ‘systems design’ to specific attributes in engineering models).
• Implement Retrieval-Augmented Generation (RAG) pipelines to enable high-accuracy querying of technical documentation and historical project data while minimizing hallucination risks in generated outputs.
• Develop time-series forecasting models to predict spend categories and material demand by integrating internal ERP data with external macroeconomic signals for supply chain optimization.
• Build machine learning classifiers to categorize supplier risks and operational anomalies, integrating diverse data sources to generate dynamic risk scores and operational insights.
• Design and oversee robust data extraction pipelines to transform raw data from Data Lakehouse environments, external web sources, SAP databases, and other systems into actionable features for predictive modeling and automated rule validation.
• Collaborate with backend engineers to integrate AI models into cohesive compliance and risk engines, ensuring seamless programmatic invocation via well-documented APIs.
• Optimize model performance to handle large-scale datasets and high-volume processing (e.g., analyzing thousands of supplier records) within operational time frames, leveraging batching or asynchronous processing where necessary.
• Validate model outputs against test cases and historical data, debugging false positives/negatives to refine algorithms and ensure defense-grade reliability and accuracy in all applications.

• 5+ years of experience in Data Science or Machine Learning, with a proven track record of deploying models into production environments.
• Expert…