Analyst

Location: Riyadh, KSA.

Years of Experience: 3-5 years.

Project Duration: 1 year.

Language Requirements: Fluency in Arabic & English (written and spoken).



We are seeking highly skilled Data Analysts with 3-5 years of experience to join our team for a 1-year engagement. The ideal candidates will bring expertise in data analytics, with experience working with large datasets, and possess strong proficiency in programming languages like SQL and visualization tools like PowerBI. Having a background in the utilities or telecom sectors and having previous experience in Saudi Arabia are highly desired. These roles offer an exciting opportunity to contribute to meaningful, data-driven projects in a dynamic and collaborative environment.

Key Qualifications:

• 3-5 years of experience in data analytics.
• Proficiency in handling and analyzing large datasets.
• Proven experience in programming languages like SQL and visualization tools like PowerBI.
  
  

Preferred Qualifications:

• Experience in revenue assurance.
• Experience in the utilities or telecom sectors.
• Previous experience working in Saudi Arabia.
  
  

Other Qualifications:

• Strong problem-solving skills with the ability to synthesize data into actionable insights.
• Excellent communication skills to present findings and recommendations effectively.
  
  

Key Responsibilities:

• Perform advanced data analytics to support revenue assurance initiatives, focusing on identifying anomalies, trends, and opportunities for improvement.
• Work with large datasets, ensuring data accuracy, consistency, and reliability for analysis and reporting.
• Develop and maintain analytical solutions using programming languages such as SQL.
• Design, implement, and manage dashboards and reports using visualization tools like Power BI to communicate insights effectively to stakeholders.
• Collaborate with cross-functional teams to understand business requirements and translate them into actionable analytical models.
• Provide data-driven recommendations to improve operational efficiency and optimize revenue streams.