Lead Specialist, Data Science & Artificial Intelligence

Why This Role Matters What You Will Deliver AI Solution Development & Innovation Model Performance & Optimization Generative AI & LLM Enablement Data Preparation & Engineering Enablement AI Operations & Lifecycle Management Governance, Risk & Responsible AI What Success Looks Like Minimum Qualifications Experience Skills That Matter Functional Expertise Business & Delivery People & Collaboration

The Senior Specialist, Data Science & Artificial Intelligence II accelerates business value creation through the application of advanced analytics, machine learning, and Generative AI solutions.

The role transforms data into actionable intelligence that improves decision-making, operational performance, automation, innovation, and business outcomes across the enterprise.

The role enables Ma’aden to harness the power of AI by developing scalable, reliable, and responsible solutions that address complex business challenges.

Through the deployment of machine learning models and GenAI applications, the role improves efficiency, enhances user experiences, and unlocks new opportunities for digital transformation.

By combining technical expertise with governance, security, and ethical AI practices, the role ensures that AI solutions deliver measurable value while maintaining trust, compliance, and sustainable adoption across the organization.

• Develop and deploy machine learning, deep learning, and Generative AI solutions that address strategic and operational business challenges.
• Design scalable AI applications that improve decision-making, productivity, automation, and business performance.
• Accelerate AI adoption through innovative use of advanced analytics and emerging AI technologies.
• Improve model accuracy, reliability, and effectiveness through feature engineering, tuning, evaluation, and optimization techniques.
• Strengthen AI outcomes through robust testing, validation, and continuous performance enhancement.
• Ensure AI solutions remain aligned with business objectives and evolving operational requirements.
• Build and enhance GenAI applications using prompt engineering, retrieval-augmented generation (RAG), and large language model technologies.
• Improve response quality, accuracy, and relevance through structured evaluation and optimization approaches.
• Deliver enterprise-ready AI capabilities that support knowledge discovery, content generation, and intelligent automation.
• Transform structured and unstructured data into high-quality datasets suitable for AI and machine learning applications.