About the Role

Enterprise Value Management Analyst focus on customer value management (CVM) within the telecom and B2B business landscape. The role is ideal for an experienced data analyst who thrives in a data-driven environment, working to uncover insights and drive revenue growth. This position offers the opportunity to contribute to strategic initiatives, identify new revenue streams, and support the culture of data-driven decision-making.

Responsibilities:

• Data Analysis: Perform advanced data analysis to identify customer behavior patterns, revenue opportunities, and market trends.

• Customer Value Management (CVM): Support the development and execution of CVM strategies to enhance customer lifetime value and retention.

• Revenue Optimization: Use statistical methodologies to analyze and identify new revenue streams and growth opportunities.

• Advanced Analytics: Apply predictive modeling, segmentation, and data visualization techniques to derive actionable business insights.

• Campaign Effectiveness: Evaluate marketing campaigns' performance and provide data-backed recommendations for improvement.

• Stakeholder Collaboration: Work closely with cross-functional teams to present insights and contribute to data-driven decision-making.

What We Need From You

To be considered for the position, you will need to meet with all of the below requirements:

• 3–5 years of experience as a data analyst, preferably in telecom, B2B, or related industries.

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related field. A Master’s degree is a plus.

Skills:

• Proficiency in Python, R, and SAS for statistical modeling and data analysis.

• Strong SQL skills for querying and manipulating large datasets.

• Experience with data visualization tools like Tableau, Power BI, or similar platforms.

• Knowledge of ETL processes and familiarity with cloud platforms such as AWS, GCP, or Azure is an advantage.

• Proficiency in statistical techniques (e.g., regression analysis, clustering, forecasting).

• Experience in predictive modeling and customer segmentation.

• Understanding of database marketing, campaign analytics, and CRM tools.

• Familiarity with telecom or B2B customer lifecycle and market dynamics is highly preferred.

• Strong problem-solving and critical-thinking abilities.

• Excellent communication skills to present complex data insights in a clear and concise manner.

• Detail-oriented and organized, with the ability to manage multiple priorities effectively.