Expert Data Scientist

Role Summary

The Expert Data Scientist is responsible for developing advanced AI and machine learning models, performing complex data analysis, designing end-to-end AI solutions, and supporting technical teams in delivering data-driven initiatives. The role requires strong technical expertise, analytical depth, and the ability to translate data into impactful solutions.

• Solution Implementation
• Technical Project Support
• Documentation & Reporting
• Data Analysis & Modeling
• Collect, clean, transform, and analyze data from different sources.
• Perform exploratory data analysis (EDA) to identify trends and patterns.
• Design, develop, and validate machine learning and AI models.
• Select appropriate algorithms and techniques for each use case.
• Evaluate model performance using industry-standard metrics (Accuracy, Precision, Recall, F1, AUC).
• Optimize and fine-tune models to enhance performance.
• Deploy machine learning models into production environments.
• Collaborate with Data Engineers and MLOps engineers on pipelines and deployment workflows.
• Build scalable data pipelines for processing large datasets.
• Monitor and update deployed models to ensure continuous performance.
• Provide expert consultation on AI solutions and model design.
• Identify required data sources and support the data acquisition process.
• Participate in technical discussions with clients and internal teams.
• Support User Acceptance Testing (UAT) from a technical perspective.
• Document modeling processes, methodologies, and analytical results.
• Prepare technical reports and present findings clearly to technical and non-technical audiences.
• Maintain proper documentation for model design and deployment.

• Language Requirement:
  Fluent Arabic (mandatory)
• Experience Level: 5+ years in Data Science / AI / Machine Learning
• Sector: AI projects, digital transformation, advanced analytics
• Education:
  
  Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, or a related field
• Preferred
  
  Certifications:
  • Machine Learning / Deep Learning
  • Data Science Certifications
  • AI & ML specializations

• Deep knowledge of machine learning, deep learning, and data science methodologies.
• Strong proficiency in Python (essential).
• Experience with ML and data libraries:
  Tensor Flow or PyTorch, Scikit-learn, Pandas, Num Py.
• Hands‑on experience with visualization tools:
  Power BI, Tableau.
• Understanding of MLOps concepts and data engineering fundamentals.
• Experience working with large datasets and implementing data mining techniques.

• Previous experience in Saudi Arabia (public or private sector).
• Experience in AI projects involving vision, NLP, or sensor data.
• Familiarity with end‑to‑end AI development lifecycle.