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Principal Specialist, Data Science & Analytics

Location: Riyadh, Saudi Arabia

Job ID: 7663

Full time

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Description

Maaden, established in 1997, is one of the fastest-growing mining companies in the world and the largest multi-commodity mining and metals company in the Middle East. We are leading the development of the mining industry to become the third pillar of Saudi Arabia’s economy by building a world-class, unique, and fully integrated mining value chain.

We are pleased to share an exciting opportunity for the below mentioned position. This role offers a chance to contribute to our ambitious growth and play a key part in shaping the future of mining in the Kingdom.

Job Purpose

• The Lead Specialist, Data Science & Analytics, acts as a technical leader and senior practitioner, driving development, deployment, and scaling of Machine Learning, AI, and advanced analytics solutions across Maaden.

• The role ensures analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions.

• Lead Specialist, Data Science & Analytics is to analyze data, extract insights, and build predictive models that help organizations make smarter decisions and solve difficult problems. By blending expertise in statistics, computer science, and business strategy, they not only analyze complex datasets but also build predictive models that improve operations and shape long-term decisions. With nearly every industry leaning on data today, the demand for skilled professionals continues to grow

Key Accountabilities:

1. Lead End-to-End Data Science Delivery

• Developing, implementing and maintaining databases and data collection systems

• Own the full lifecycle of ML/AI initiatives - from problem framing, data exploration, feature engineering, model development, validation, and MLOps handover.

• Deliver scalable and production-grade models, ensuring alignment with enterprise data governance and AI standards.

• Performing statistical analysis to understand and interpret data insights

• Applying data mining techniques to identify patterns, trends, and relationships in large datasets

• Building predictive models and machine learning algorithms to forecast future outcomes

• Creating clear data visualizations and reports to communicate findings to stakeholders

• Working with cross-functional teams to understand business needs and provide data-driven solutions

• Design and maintain reliable data pipelines and models in partnership with data engineering to ensure data is accurate, timely, and trustworthy for downstream use

• Ensuring data security and compliance with relevant regulations

• Drive experimentation, model versioning, automated retraining, and continuous improvement.

2. Translate Business Needs into AI/Analytics Solutions

• Establish frameworks and operating models that make data science accessible, scalable, and embedded within business and technical functions

• Engage BU/domain stakeholders to identify value creation opportunities and convert them into actionable analytics use cases.

• Build value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data & AI leadership and business teams.

3. Industrialize AI/ML Models (ML Ops & Architecture)

• Partner with data engineering, data platforms, and cloud/OT architecture teams to embed models into enterprise systems and operational layers.
• Set standards for production deployment, testing, monitoring, drift handling, and lifecycle governance.
• Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins
• Leverage machine learning, optimization, and computer vision as enabling tools for performance, reliability, and sustainability improvements

4. Responsible AI, Quality & Governance

• Ensure compliance with Maaden’s Responsible AI, data quality, and data governance frameworks.
• Promote reproducibility, documentation, lineage tracking, and auditability across all data science assets.
• Ensure transparency, explainability, and continuous model governance across production and enterprise environments

5. Stakeholder Management & Value Realization

• Communicate insights, results, risks, and recommendations to decision-makers using compelling narratives and visual

Apply directly at Ma'aden