×
Register Here to Apply for Jobs or Post Jobs. X

Senior Specialist, Data Science & Artificial Intelligence

Job in Riyadh, Riyadh Region, Saudi Arabia
Listing for: Ma'aden Aluminium Company (MAC)
Full Time position
Listed on 2026-09-11
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Business & Operations, Data Scientist
Salary/Wage Range or Industry Benchmark: 280000 - 420000 SAR Yearly SAR 280000.00 420000.00 YEAR
Job Description & How to Apply Below

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…

Position Requirements
10+ Years work experience
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)
0
200
Filters
Education Level
Experience Level (years)
Posted in last:
Salary