Senior Specialist, Data Science & Artificial Intelligence

Ma'aden Aluminium Company (MAC); Riyadh; On-site; SAR 280,000 - 420,000; Full time

Job summary

Ma'aden Aluminium Company (MAC) seeks a Senior Specialist Data Science & AI II to accelerate business value through advanced analytics, ML, and GenAI. You will design, deploy, and govern AI solutions across the enterprise, ensuring secure, scalable, and responsible AI implementations.

You will lead data preparation, model development, validation, and lifecycle management, collaborating with stakeholders to drive automation, performance, and digital transformation initiatives at scale.

Qualifications

• Bachelor's degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative discipline.
• Experience 4-6 years of experience in data science, machine learning, artificial intelligence, or advanced analytics roles.
• Experience developing and deploying machine learning and AI solutions in business environments.
• Experience working with structured and unstructured data for analytical and AI use cases.
• Experience supporting AI solution deployment, monitoring, and model lifecycle management.

Responsibilities

• Develop and deploy machine learning, deep learning and Generative AI solutions that address strategic and operational business challenges.
• Design scalable AI applications that improve decision-making, productivity, automation and business performance.
• Accelerate AI adoption through innovative use of advanced analytics and emerging AI technologies.
• Improve model accuracy, reliability and effectiveness through feature engineering, tuning, evaluation and optimization techniques.
• Build and enhance GenAI applications using prompt engineering, retrieval-augmented generation (RAG) and large language model technologies.
• Transform data into high-quality datasets for AI/ML, ensuring governance, reliability and business relevance.

Skills

Machine Learning

Deep Learning

Generative AI

LLMs

Prompt Engineering

RAG

Model Fine-Tuning

Data Preparation

Feature Engineering

MLOps

LLMOps

AI Deployment

API Integration

Model Monitoring

Education

Bachelor's degree in Data Science, AI, CS

Tools

TensorFlow

PyTorch

Scikit-Learn

Python

SQL

Job description

Why This Role Matters

The Senior Specialist Data Science & Artificial Intelligence II accelerates business value creation through the application of advanced analytics machine learning and Generative AI solutions The role transforms data into actionable intelligence that improves decision-making operational performance automation innovation and business outcomes across the enterprise The role enables Ma aden to harness the power of AI by developing scalable reliable and responsible solutions that address complex business challenges Through the deployment of machine learning models and GenAI applications the role improves efficiency enhances user experiences and unlocks new opportunities for digital transformation By combining technical expertise with governance security and ethical AI practices the role ensures that AI solutions deliver measurable value while maintaining trust compliance and sustainable adoption across the organization

What You Will Deliver

• strong AI Solution Development amp Innovation strong Develop and deploy machine learning deep learning and Generative AI solutions that address strategic and operational business challenges Design scalable AI applications that improve decision-making productivity automation and business performance Accelerate AI adoption through innovative use of advanced analytics and emerging AI technologies
• strong Model Performance amp Optimization strong Improve model accuracy reliability and effectiveness through feature engineering tuning evaluation and optimization techniques Strengthen AI outcomes through robust testing validation and continuous performance enhancement Ensure AI solutions remain aligned with business objectives and evolving operational requirements
• strong Generative AI amp LLM Enablement strong Build and enhance GenAI applications using prompt engineering retrieval-augmented generation RAG and large language model technologies Improve response quality accuracy and relevance through structured evaluation and optimization approaches Deliver enterprise-ready AI capabilities that support knowledge discovery content generation and intelligent automation
• strong Data Preparation amp Engineering Enablement strong Transform structured and unstructured data into high-quality datasets suitable for AI and machine learning applications Improve data usability and reliability through effective cleansing preparation and feature development practices Ensure AI solutions are built on trusted governed and business-relevant data assets
• strong AI Operations amp Lifecycle Management strong Support deployment monitoring retraining and lifecycle management of AI solutions using MLOps and LLMOps practices Improve operational reliability and scalability of production AI models and applications Enable sustainable AI adoption through effective performance monitoring and continuous improvement
• strong Governance Risk amp Responsible AI strong Ensure AI solutions comply with enterprise governance cybersecurity privacy and ethical AI requirements Strengthen transparency and trust by documenting models assumptions risks and validation outcomes Promote responsible AI practices that balance innovation with risk management and compliance obligations

Success Looks Like

AI and machine learning solutions deliver measurable business value and operational improvement Generative AI applications provide accurate reliable and high-quality outputs for end users Machine learning models achieve performance targets and remain effective throughout their lifecycle AI solutions are successfully integrated into enterprise processes and systems MLOps and LLMOps practices improve model reliability scalability and operational efficiency Governance security and responsible AI requirements are consistently embedded within AI initiatives

Requirements

Bachelor's degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative discipline.Experience 4 6 years of experience in data science, machine learning, artificial intelligence, or advanced analytics roles.Experience developing and deploying machine learning and AI solutions in business environments.Experience working with structured and unstructured data for analytical and AI use cases.Experience supporting AI solution deployment, monitoring, and model lifecycle management.Functional Expertise Machine Learning & Deep Learning, Generative AI & Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), Model Fine-Tuning & Evaluation, Data Preparation & Feature EngineeringBusiness & Delivery Python & SQL, TensorFlow, PyTorch & Scikit-Learn, MLOps & LLMOps Practices, API Integration & AI Deployment, Model Monitoring & Performance Optimization, Analytical Problem SolvingPeople & Collaboration Collaboration & Teamwork, Stakeholder Engagement, Communication & Knowledge Sharing, Results Orientation, Accountability, Continuous Improvement