Lead Specialist Data Science & Analytics II📣 Job Ad

About the Lead Specialist, Data Science & Analytics II Role

Maaden, established in 1997, is a rapidly growing global mining company and the largest multi-commodity mining and metals entity in the Middle East. This full-time position in Riyadh offers a significant opportunity to contribute to the development of Saudi Arabia's mining industry and shape its future value chain.

Role Purpose and Scope

The Lead Specialist, Data Science & Analytics II serves as a technical leader responsible for the development, deployment, and scaling of advanced analytics, Machine Learning, and AI solutions across Maaden. This role ensures that analytics products are designed, validated, industrialized, governed, and adopted effectively to deliver measurable value across mining, processing, operations, and enterprise functions. The core function involves analyzing data to extract insights and build predictive models that support informed decision-making and address complex business challenges.

Key Responsibilities

• Lead the end-to-end delivery of data science initiatives, including problem framing, data exploration, feature engineering, model development, validation, and handover for MLOps.
• Develop, implement, and maintain databases and data collection systems, ensuring data accuracy, timeliness, and trustworthiness.
• Perform statistical analysis and apply data mining techniques to identify patterns, trends, and insights within large datasets.
• Build predictive models and machine learning algorithms to forecast future outcomes and drive continuous improvement through experimentation and automated retraining.
• Translate business needs into actionable AI/Analytics solutions by establishing frameworks and operating models for data science accessibility and scalability.
• Collaborate with business stakeholders to identify value creation opportunities and define use cases, success criteria, and solution roadmaps.
• Partner with data engineering and architecture teams to industrialize AI/ML models, ensuring seamless integration into enterprise systems and operational layers.
• Set standards for production deployment, testing, monitoring, and lifecycle governance of models.
• Ensure compliance with Responsible AI, data quality, and data governance frameworks, promoting transparency, explainability, and auditability.
• Communicate findings, results, risks, and recommendations to decision-makers through compelling narratives and visualizations.
• Track value realization and adoption metrics to ensure measurable business impact.

Qualifications and Experience

Candidates should possess a Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or a related field. A minimum of 6 years of experience in Data Science or Advanced Analytics is required, with a preference for experience in industrial, mining, or heavy-asset environments. This includes 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 is essential.

Strong proficiency with modern ML frameworks (TensorFlow, PyTorch) and cloud platforms (Azure, AWS) is necessary. Technical fluency with modern analytics stacks, data modeling, SQL, and effective partnership with engineering teams are also required.

Technical Skills and Capabilities

• Hands-on experience developing and deploying machine learning models for time-series forecasting, predictive modeling, and optimization use cases.
• Practical experience with Generative AI solutions, including copilots, intelligent automation, and agent-based workflows.
• Strong understanding of model performance, validation, stability, and business impact.

Experience with data pipelines across IT and OT environments, sensor data, streaming data processing, and industrial data sources is beneficial. Familiarity with MLOps/AgentOps, including model deployment, lifecycle management, monitoring, retraining, versioning, and drift management, is also advantageous.

Work Environment and Core Competencies

This is a full-time position based in Riyadh. Core competencies for this role include ensuring Model Accuracy & Reliability, driving Adoption & Business Impact, achieving Delivery Velocity, and maintaining Compliance & Quality aligned with Responsible AI and governance standards.