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.
Key Responsibilities
2. Solution Implementation
3. Technical Project Support
4. Documentation & Reporting
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Data Analysis & Modeling
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Collect, clean, transform, and analyze data from different sources.
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Perform exploratory data analysis (EDA) to identify trends and patterns.
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Design, develop, and validate machine learning and AI models.
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Select appropriate algorithms and techniques for each use case.
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Evaluate model performance using industry-standard metrics (Accuracy, Precision, Recall, F1, AUC).
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Optimize and fine-tune models to enhance performance.
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Deploy machine learning models into production environments.
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Collaborate with Data Engineers and MLOps engineers on pipelines and deployment workflows.
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Build scalable data pipelines for processing large datasets.
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Monitor and update deployed models to ensure continuous performance.
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Provide expert consultation on AI solutions and model design.
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Identify required data sources and support the data acquisition process.
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Participate in technical discussions with clients and internal teams.
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Support User Acceptance Testing (UAT) from a technical perspective.
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Document modeling processes, methodologies, and analytical results.
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Prepare technical reports and present findings clearly to technical and non-technical audiences.
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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
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Data Science Certifications
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AI & ML specializations
Required Skills & Expertise
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Deep knowledge of machine learning, deep learning, and data science methodologies.
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Strong proficiency in:
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Experience with ML and data libraries:
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TensorFlow or PyTorch
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Scikit-learn
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Pandas, NumPy
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Hands-on experience with visualization tools:
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Understanding of MLOps concepts and data engineering fundamentals.
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Experience working with large datasets and implementing data mining techniques.
Preferred Experience
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Previous experience in Saudi Arabia (public or private sector).
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Experience in AI projects involving vision, NLP, or sensor data.
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Familiarity with end-to-end AI development lifecycle