Principal Specialist Data Science & Artificial Intelligence

About Ma'aden and the Role

Ma'aden, established in 1997, is a rapidly expanding multi-commodity mining and metals company in the Middle East. It plays a key role in developing Saudi Arabia's mining industry. This full-time role, based in Riyadh, is for a Principal Specialist in Data Science & Artificial Intelligence within the Agentic AI department. The specialist will lead advanced data science and analytics initiatives, translating business challenges into scalable analytical solutions, AI-enabled insights, predictive models, and decision intelligence products.

Key Responsibilities

• Translate business priorities and operational challenges into clear data science problem statements, analytical approaches, and measurable outcomes.
• Design and deliver predictive, prescriptive, diagnostic, and exploratory analytics solutions to support decision-making across business and operational domains.
• Develop machine learning models, statistical analyses, simulations, optimization approaches, and advanced analytics products using enterprise data assets.
• Support the development of agentic AI use cases by defining data, model, workflow, evaluation, and decision-support requirements.
• Collaborate with AI engineers, platform teams, data engineers, and business stakeholders to embed analytics and machine learning into autonomous or semi-autonomous workflows.
• Create reusable analytical assets, data science patterns, feature logic, model components, and decision intelligence products that can scale across business domains.
• Partner with data platform, governance, and architecture teams to ensure data products are trusted, well-documented, reusable, and operationally maintainable.
• Apply appropriate data science governance practices for model validation, performance monitoring, bias checks, versioning, deployment readiness, and lifecycle management.
• Provide expert guidance to analysts, data scientists, engineers, and business teams on analytical methods, model design, evaluation, and adoption.
• Advise stakeholders on what analytics or AI can realistically solve, required data readiness, implementation complexity, and expected value.

Model Quality and Governance

The role involves defining evaluation approaches for AI-enabled insights, model performance, business impact, human oversight, and continuous improvement. This includes promoting responsible use of agentic AI by ensuring transparency, explainability, control, auditability, and fit-for-purpose model deployment. The specialist will also define success measures, impact metrics, adoption criteria, and benefit tracking approaches for analytics and AI-enabled solutions, ensuring compliance with data governance, cybersecurity, privacy, and responsible AI expectations.

Data Product Advancement

This position is responsible for integrating analytics into dashboards, workflows, applications, copilots, and AI agents where decision support can improve speed, quality, and productivity. Maintaining clear documentation covering assumptions, data sources, model logic, limitations, controls, and expected business usage is also a key aspect of this role.

Technical Leadership and Stakeholder Advisory

The Principal Specialist will review analytical designs, model outputs, assumptions, and recommendations to ensure technical quality and business relevance. Effective communication of insights, risks, limitations, and recommended actions to technical, operational, and executive stakeholders is essential.

Qualifications and Experience

• Over 10 years of relevant experience in data science and artificial intelligence.
• Demonstrated ability to translate business problems into clear data science use cases and analytical approaches.
• Experience in delivering predictive, prescriptive, and decision intelligence solutions with strong technical quality and business relevance.
• Proficiency in supporting Agentic AI use cases with trusted data, robust models, evaluation methods, and controls.
• Capability to ensure analytics and AI products are reusable, documented, governed, monitored, and aligned with responsible AI expectations.