Senior Data Scientist

Role overview

Data science and analytics work

• Analyze large and complex datasets to identify trends, patterns, and business opportunities.
• Develop and deploy statistical, predictive, and machine learning models; select algorithms, optimize performance, and evaluate models with appropriate metrics.
• Clean and preprocess data, engineer features, and perform exploratory data analysis.
• Build forecasting, classification, regression, clustering, and optimization models.
• Translate business requirements into analytical solutions and collaborate with Data Engineers, AI Engineers, Business Analysts, and stakeholders.
• Develop dashboards, reports, and visualizations to communicate findings.
• Deploy and monitor models in production; ensure data quality, reproducibility, scalability, and model documentation.
• Support advanced analytics, AI initiatives, and continuous improvement of existing models.

Benefits

• Family medical insurance covers the employee and eligible family members.
• Airline tickets are provided for the employee, spouse, and up to two children.
• Company-provided Iqama sponsorship and processing in accordance with applicable regulations.

Requirements

• Analyze large and complex datasets to identify trends, patterns, and business opportunities.
• Develop and deploy statistical, predictive, and machine learning models.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
• Select appropriate algorithms, optimize model performance, and evaluate models using suitable statistical and machine learning metrics.
• Translate business requirements into data science and analytical solutions.
• Build forecasting, classification, regression, clustering, and optimization models.
• Collaborate with Data Engineers, AI Engineers, Business Analysts, and business stakeholders.
• Develop dashboards, reports, and visualizations to communicate analytical findings.
• Deploy and monitor models in production environments.
• Ensure data quality, reproducibility, scalability, and appropriate model documentation.
• Support advanced analytics, AI initiatives, and continuous improvement of existing models.