Lead Specialist, Data & Artificial Intelligence Delivery Management

Ma'aden Aluminium Company (MAC); Medina; On-site; SAR 1,200,000 - 2,400,000; Full time

Job summary

Ma'aden Aluminium Company (MAC) is seeking a Lead Specialist Data Science & Analytics to drive end-to-end ML, AI, and advanced analytics initiatives across mining, processing, and corporate functions. You will transform business problems into scalable analytical products and ensure reliable governance and platform integration.

The role emphasizes stakeholder engagement, MLOps practices, data governance, and responsible AI to deliver measurable operational and financial improvements.

Qualifications

• 6-8 years of experience in data science, machine learning, advanced analytics, or AI-related roles.
• Experience developing and deploying production-grade analytical and machine learning solutions.
• Experience translating business problems into analytical frameworks, predictive models, and actionable recommendations.

Responsibilities

• Lead the end-to-end development of ML/AI and analytics solutions addressing high-value business challenges.
• Deliver scalable production-ready models to improve operational efficiency and decision-making.
• Strengthen analytics capabilities through experimentation, model optimization, and performance improvement.
• Build partnerships with business, technology and data teams to accelerate solution adoption.

Skills

Machine Learning

Artificial Intelligence

Predictive Analytics

Statistical Modeling

Data Mining

Pattern Discovery

Feature Engineering

Model Optimization

Data Visualization

AI Solution Design

Industrialization

Business & Delivery

Python

SQL

MLOps

Model Lifecycle Management

Data Pipeline

Analytical Environment Design

Data Governance

Compliance

Stakeholder Management

Cross-Functional Collaboration

Communication

Presentation Skills

Problem Solving

Critical Thinking

Continuous Improvement

Education

Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Artificial Intelligence, or a related quantitative discipline

Tools

Python

SQL

MLOps tooling

Job description

Why This Role Matters

The Lead Specialist Data Science amp Analytics drives the development deployment and adoption of advanced analytics machine learning and AI solutions that improve operational performance business decision-making and enterprise productivity across Maaden The role transforms complex business challenges into scalable analytical solutions that generate measurable value across mining processing operations and corporate functions The role bridges business priorities with technical execution ensuring that analytical products progress efficiently from concept through deployment and industrialization By embedding AI and data science capabilities into operational processes the role accelerates digital transformation and strengthens Maaden s ability to leverage data as a strategic asset Through technical leadership governance oversight and stakeholder engagement the role ensures analytical solutions are reliable scalable compliant and aligned with enterprise standards enabling sustainable adoption and value realization across the organization

What You Will Deliver

AI amp Data Science Solution Delivery Lead the end-to-end development of machine learning AI and advanced analytics solutions that address high-value business challenges Deliver scalable production-ready models that improve operational efficiency reliability productivity and decision-making Strengthen analytical capabilities through robust experimentation model optimization and continuous performance improvement Business Value amp Use Case Development Translate business priorities into actionable analytics opportunities value hypotheses and implementation roadmaps Identify prioritize and develop AI and analytics use cases that deliver measurable operational and financial outcomes Establish clear success measures KPIs and value realization frameworks for analytical initiatives AI Industrialization amp Platform Integration Enable seamless deployment of analytical models into enterprise systems operational platforms and digital environments Strengthen model reliability and scalability through effective MLOps practices lifecycle management and monitoring standards Improve adoption and sustainability of AI solutions by ensuring technical readiness and operational integration Data Quality amp Analytical Foundations Strengthen trust in analytics through reliable governed and high-quality data foundations Partner with Data Engineering teams to improve analytical environments data pipelines and model readiness Ensure data assets meet enterprise requirements for accuracy integrity security and compliance Responsible AI amp Governance Embed responsible AI principles governance controls and quality standards across analytical solutions Strengthen transparency explainability auditability and lineage across data science assets and models Ensure compliance with enterprise data governance security and regulatory requirements Stakeholder Engagement amp Value Realization Build strong partnerships with business technology and Data amp AI stakeholders to accelerate solution adoption Communicate analytical insights risks recommendations and outcomes through compelling narratives and visualizations Measure and improve business impact through continuous tracking of adoption performance and value realization.

What Success Looks Like

Machine learning and AI solutions deliver measurable operational financial and productivity improvements Analytical products are successfully adopted and sustained across targeted business functions Models achieve required standards for performance reliability scalability and business relevance AI and analytics projects progress efficiently from concept to production deployment Data science initiatives demonstrate compliance with governance security and Responsible AI requirements Business stakeholders make faster and better decisions through trusted analytical insights and predictive capabilities.

Experience

6 8 years of experience in data science machine learning advanced analytics or AI-related roles Experience developing and deploying production-grade analytical and machine learning solutions Experience translating business problems into analytical frameworks predictive models and actionable recommendations Experience working with cross-functional business technology and data teams in complex organizational environments.

Skills That Matter

Machine Learning amp Artificial Intelligence Predictive Analytics amp Statistical Modeling Data Mining amp Pattern Discovery Feature Engineering amp Model Optimization Data Visualization amp Analytical Storytelling AI Solution Design amp Industrialization Business amp Delivery Python SQL amp Advanced Analytics Tools MLOps amp Model Lifecycle Management Data Pipeline amp Analytical Environment Design AI Product Delivery amp Value Realization Data Governance amp Compliance Performance Measurement amp KPI Development People amp Collaboration Stakeholder Management Business amp Technical Translation Cross-Functional Collaboration Communication amp Presentation Skills Problem Solving amp Critical Thinking Continuous Improvement amp Accountability

Bachelor s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Artificial Intelligence, or a related quantitative discipline.