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. 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: 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.