Principal Specialist Data Science & Analytics📣 Job Ad

About Ma'aden and the Principal Specialist Role

Ma'aden, established in 1997, is a leading multi-commodity mining and metals company in the Middle East. The company contributes to Saudi Arabia’s economy by building a world-class, fully integrated mining value chain. We are seeking a Principal Specialist, Data Science & Analytics to join our team in Riyadh. This full-time role requires 8-10 years of experience and involves acting as a technical leader and senior practitioner, driving the development, deployment, and scaling of Machine Learning, AI, and advanced analytics solutions across the organization.

Core Responsibilities and Data Science Delivery

The Principal Specialist will be responsible for ensuring analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions. Key responsibilities include:

• Leading end-to-end data science delivery, including developing and maintaining databases and data collection systems.
• Owning the full lifecycle of ML/AI initiatives, from problem framing, data exploration, feature engineering, model development, and validation to MLOps handover.
• Delivering scalable and production-grade models, ensuring alignment with enterprise data governance and AI standards.
• Performing statistical analysis and 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 and working with cross-functional teams to provide data-driven solutions.
• Designing and maintaining reliable data pipelines and models in partnership with data engineering to ensure data accuracy, timeliness, and trustworthiness.
• Driving experimentation, model versioning, automated retraining, and continuous improvement, while ensuring data security and compliance.
• Translating business needs into AI/analytics solutions by establishing frameworks, identifying value creation opportunities, and converting them into actionable use cases.
• Building value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data & AI leadership and business teams.

AI/ML Model Industrialization and Governance

This role also focuses on the industrialization and responsible governance of AI/ML models:

• Partnering with data engineering, data platforms, and cloud/OT architecture teams to embed models into enterprise systems and operational layers.
• Setting standards for production deployment, testing, monitoring, drift handling, and lifecycle governance of AI/ML models.
• Ensuring seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins, leveraging machine learning, optimization, and computer vision for performance, reliability, and sustainability improvements.
• Ensuring compliance with Ma'aden’s Responsible AI, data quality, and data governance frameworks.
• Promoting reproducibility, documentation, lineage tracking, and auditability across all data science assets, ensuring transparency, explainability, and continuous model governance.
• Communicating insights, results, risks, and recommendations to decision-makers, and tracking value realization, adoption metrics, and operational impact.

Required Qualifications and Experience

Candidates should possess the following qualifications and experience:

• A Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field.
• 8-10 years of experience in Data Science or Advanced Analytics, with a preference for industrial, mining, or heavy-asset environments.
• At least 2 years of experience leading or mentoring analytics professionals.
• Proven ability to translate business problems into analytic approaches, define hypotheses, design analyses, and synthesize results into clear recommendations.

Technical Expertise and Platform Proficiency

The role requires strong technical fluency and practical experience with various platforms and tools:

• Strong proficiency with modern ML frameworks and cloud platforms such as TensorFlow, PyTorch, Azure, and AWS, including experience with Microsoft AI Factory.
• Technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.
• Hands-on experience developing and deploying machine learning models, including time-series forecasting, predictive modeling, and optimization use cases.
• Strong understanding of model performance, validation, stability, and business impact.
• Practical experience with Generative AI solutions, including copilots, intelligent automation, and agent-based workflows, with the ability to embed GenAI capabilities into enterprise processes.
• Experience working with enterprise cloud platforms, preferably Microsoft Azure Data Platform, Databricks AI Platform, and Microsoft AI Foundry / Microsoft AI Factory.
• Understanding of cloud-native architectures for scalable analytics and AI solutions.

Desired Capabilities and Core Competencies

Additional capabilities and core competencies are valued for this position:

• Experience designing and maintaining data pipelines across IT and OT environments, with exposure to sensor data, streaming/real-time data processing, and industrial data sources.
• Ability to collaborate with data engineering teams to ensure reliable, timely, and trusted data flows.
• Experience in MLOps / AgentOps, including model deployment and lifecycle management, monitoring, retraining, versioning, and drift management.
• Familiarity with automation and operationalization of ML/AI workloads.
• Core competencies include ensuring model accuracy and reliability, driving adoption and business impact, maintaining delivery velocity, and ensuring compliance with Responsible AI, governance, and documentation standards.