Reports To: Manager - Business Planning Analysis and Reporting
Division: Customer Relations & Experience
Mission
To Analyze large datasets to develop and maintain predictive analytics solutions, generating customer insights, enhancing customer experience, and ensuring effective system support and model performance.
Description
Extract, analyse and interpret Customer data and advanced analytical models to generate insight to aid the execution of various Customer Relations and Experience strategies.
Collect and analyze customer and business information and trends for forecasting and planning across all channels (Call Center, Walk In, Self Service, Social Media/ Digital, Account Management).
Evaluate various Customer Relations programmes and conduct behavioural, data mining, customer insight generation, predictive modeling, performance management, and other relevant statistical analyses related to proposed and current Customer Relations programmes
Ensure generation of relevant Customer Services report (daily, weekly and monthly across all regions, segment and channels) for management decision making
purposes.
Audit and review of Customer Relations data to ensure data integrity and adherence to data governance policies.
Conduct competitive intelligence on products and service offerings across all regions, segment and channels.
Provide data and analysis to support the business planning process by management.
Forecasting, projections and trend analysis for traffic volumes and flow to the Call Center.
Workforce dimensioning and scheduling for internal call center helpdesks.
Liaise with outsourced call center vendors to produce and validate customer traffic and Call center performance reports.
Requirements
Education
First degree in any relevant discipline
Fluent in English.
Experience
3-7 years’ experience which includes
Experience working in a medium organization
Solid understanding of predictive analysis: predictive modelling, machine learning and data mining.
Proficient in using two programming languages out of R, python 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.