Lead and manage multidisciplinary teams including data analysts, data engineers, business intelligence developers, data scientists, and data application specialists while fostering a high-performance and collaborative work environment.
Develop and implement data analytics and AI strategies aligned with organizational objectives to support business growth and operational improvement.
Oversee the analysis of complex datasets to identify trends, patterns, and actionable insights for stakeholders.
Supervise the development and implementation of predictive models, machine learning algorithms, and statistical methods to address business challenges.
Ensure the creation of effective dashboards, reports, and visualizations that communicate insights clearly to both technical and non-technical stakeholders.
Establish data governance standards and data quality policies to ensure accuracy, consistency, and reliability across analytics operations.
Collaborate closely with business leaders and stakeholders to understand data needs and provide strategic recommendations that support decision-making.
Monitor and evaluate the performance of data analytics initiatives and identify opportunities for continuous improvement and operational efficiency.
Mentor and support team members to enhance their technical and professional capabilities in data analytics and AI.
Stay updated on emerging trends, technologies, and best practices in data science, analytics, and artificial intelligence to strengthen team capabilities and innovation.
Qualifications
Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Artificial Intelligence, or a related field; Master’s or PhD degree preferred.
Minimum of 4–6 years of professional experience, including at least 2 years in a related or supervisory role.
Strong knowledge of data analytics, machine learning, statistical modeling, and artificial intelligence concepts.
Experience in managing and leading analytics or AI teams in a collaborative environment.
Proficiency in programming languages such as Python, R, and SQL for data analysis, modeling, and data processing.
Knowledge of data governance principles, data quality management, and analytics best practices.
Strong analytical thinking and problem-solving skills with the ability to manage complex data challenges.
Ability to translate technical findings into business insights and communicate effectively with both technical and non-technical stakeholders.
Experience in project management, strategic planning, and performance monitoring.
Familiarity with organizational systems, policies, compliance requirements, and operational frameworks.
Strong communication, presentation, leadership, and stakeholder management skills.
Commitment to ethical data practices and compliance with data privacy regulations.
Knowledge of financial data analysis, predictive analytics, and risk measurement concepts is considered an advantage.
نحن نستخدم ملفات تعريف الارتباط لضمان حسن سير عمل موقعنا. للحصول على تجربة زيارة محسنة ، نستخدم منتجات التحليل. يتم استخدامها عندما توافق على "الإحصائيات".بيان الخصوصية