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.
Key Responsibilities 1.
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.
2. Solution Implementation 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.
3. Technical Project Support 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.
4. Documentation & Reporting 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 Required Skills & Expertise Deep knowledge of machine learning, deep learning, and data science methodologies.
Strong proficiency in: Python (essential) Experience with ML and data libraries: TensorFlow or PyTorch Scikit-learn Pandas, NumPy 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.
Preferred Experience 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.