Job Description

Roles & Responsibilities

Responsibilities:

• 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.

Desired Candidate Profile

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.