Analyst – CVM Analytics, Marketing at MTN Nigeria

MTN Nigeria – The leader in telecommunications in Nigeria, and a part of a diverse community in Africa and the Middle East, our brand is instantly recognisable. It is through our compelling brand that we are able to attract the right talents who we carefully nurture by continuously improving our employment offerings even beyond reward and recognition.

We are recruiting to fill the position below:

Job Title: Analyst – CVM Analytics, Marketing

Job Identification: 1635
Location: Ikoyi, Lagos
Job Category: MTN Level 2
Job Schedule: Full time
Reports To: Manager CVM Analytics
Division: Marketing

Description

  • Extract, analyze and interpret data and advanced analytical models to generate insight to aid marketing strategy and product development and implementation
  • Work with campaign management team to understand customer needs and develop proactive and innovative data driven solutions and campaigns
  • Analyze micro-profiles of all market segments, design models using customer profile attributes, and develop multiple scenarios to illustrate behavior patterns in creating, targeting, and positioning campaign strategies.
  • Conduct analyses with focus on experimental design, assessment, execution, and measurement of current marketing programs.
  • Evaluate proposed marketing programs and conduct behavioral, data mining, customer segmentation, predictive modelling, performance management, and other relevant statistical analyses related to proposed and current marketing programs.
  • Work closely with CVM stakeholders to understand and maintain focus on their analytical needs, including identifying critical metrics and KPIs, and deliver actionable insights to relevant decision makers.
  • Summarize analytics findings and integrate with non-traditional data sources when appropriate, to enhance campaign development initiatives
  • Develop and use all relevant metrics and measures to continually monitor inactivity and revenue generating base and take appropriate actions to ensure consistent usage and reduce inactivity.
  • Conduct analysis and present findings leading to improved customer identification, attraction and retention techniques and methodologies
  • Collect, analyze, interpret, and summarize data in preparation for generation of statistical and analytical reports and provide intelligence that supports decision-making.
  • Proactively analyze data to answer key questions from stakeholders or out of shelf curiosity with an eye for what drives business performance, investigating and communicating areas for improvement in efficiency and productivity
  • Support CVM commercial team to identify opportunity base for campaign creation.
  • Utilize specified statistical software to analyze and interpret research data, as appropriate to the individual position.
  • Understand customer demographics, usage, and behavior to drive decision making on retention and value creation.
  • Provide support to campaign segmentation analyst as required.
  • Contribute and participate in campaign idea generation meetings and cross functional Customer Lifecycle Management meeting as required

Job Requirements
Education:

  • First Degree in Mathematics, Computer Science, Engineering, Marketing or other Social Science disciplines.
  • Fluent in English.

Experience:
3 – 7 years’ experience which includes:

  • Experience working in a medium-sized organization.
  • Solid understanding of predictive analysis: predictive modelling, machine learning and data mining.
  • Proficient in using two programming languages out of R, python, SAS and SQL
  • Good understanding of customer data analysis, propensity modelling and segmentation techniques; excellent understanding of data manipulation and interrogation techniques.
  • Good knowledge of statistical modeling techniques and algorithms.

Deadline: 19th October, 2022 (11:59 PM).

Method of Application
Interested and qualified candidates should:
Click here to apply online


Comments

Leave a Reply

Your email address will not be published. Required fields are marked *