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.
- 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.
Requirements
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:
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Machine Learning / Deep Learning
- Data Science Certifications
- AI & ML specializations
Required Skills & Expertise
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Deep knowledge of machine learning, deep learning, and data science methodologies.
- Strong proficiency in:
- Experience with ML and data libraries:
- TensorFlow or PyTorch
- Scikit-learn
- Pandas, NumPy
- Hands-on experience with visualization tools:
- 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.