Revenue Enhancement Analyst

1 day ago


Kuwait City, Al Asimah Zain Bahrain Full time

Zain Bahrain has been at the forefront of mobile telecommunications in the Middle East since its inception in 1983. With our expansion strategy initiated in 2003, we have witnessed remarkable growth.

About the Job

We are seeking a skilled data analyst to fill the position of Enterprise Value Management Analyst. This role is pivotal in our customer value management (CVM) strategy within the telecom and B2B sectors. As a seasoned professional, you will utilize your expertise to drive revenue growth and uncover valuable insights.

Main Responsibilities:

  1. Data Analysis: Perform comprehensive data analysis to identify customer behavior patterns, revenue opportunities, and market trends.
  2. Customer Value Management (CVM): Collaborate with our team to develop and implement CVM strategies that enhance customer lifetime value and retention.
  3. Revenue Optimization: Use statistical methods to analyze and identify new revenue streams and growth opportunities.
  4. Advanced Analytics: Apply predictive modeling, segmentation, and data visualization techniques to derive actionable business insights.
  5. Campaign Effectiveness: Evaluate marketing campaigns' performance and provide data-driven recommendations for improvement.
  6. Collaboration: Work closely with cross-functional teams to present insights and contribute to data-driven decision-making.
Requirements

To be considered for this position, you must meet the following requirements:

  1. 3–5 years of experience in data analysis, preferably in telecom, B2B, or related fields.
  2. Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related field. A Master's degree is an added advantage.

Essential Skills:

  1. Proficiency in Python, R, and SAS for statistical modeling and data analysis.
  2. Strong SQL skills for querying and manipulating large datasets.
  3. Experience with data visualization tools like Tableau, Power BI, or similar platforms.
  4. Knowledge of ETL processes and familiarity with cloud platforms such as AWS, GCP, or Azure is beneficial.
  5. Proficiency in statistical techniques (e.g., regression analysis, clustering, forecasting).
  6. Experience in predictive modeling and customer segmentation.
  7. Understanding of database marketing, campaign analytics, and CRM tools.
  8. Familiarity with telecom or B2B customer lifecycle and market dynamics is highly advantageous.
  9. Strong problem-solving and critical-thinking abilities.
  10. Excellent communication skills to present complex data insights clearly and concisely.
  11. Attention to detail and organizational skills to manage multiple priorities effectively.


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