Senior Analyst: M-Pesa Financial Operations and Data Analytics Full-Time

Role purpose:

Implementation and maintenance of RA controls to detect, deter and prevent revenue leakages due to systems configurations and shortfalls in processes in the M-Pesa Eco-System. Drive the implementation and adoption of data analytics and new approaches like Machine Learning and Artificial Intelligence to generate meaningful business insights. Drive and coordinate Finance Team digital initiatives through the digital transformation journey.

Key accountabilities and decision ownership

•  End to End Reconciliations of ALL M-Pesa Transactions within the Eco-system and with all third parties;
• Drive the P & L coverage model for RA – map all controls to the P & L entries, specifically for M-Pesa costs and revenues;
• Define new (and maintain existing) use cases for Machine Learning and Artificial Intelligence – report on business insights to Management;
• Monthly reporting on Revenue leakages and revenue losses prevented;
• Track and coordinate the Finance Journey on Digital Transformation

Core competencies, knowledge and experience

• At least 3 years of experience with regard to Billing, Revenue Assurance and/or Fraud management or related areas in telecommunications, banking or utilities companies;
• Strong understanding of telecommunications and Mobile Money services – Network Events and Accounting of such;
• Good understanding of financial principles, understands financial ratios, can interpret standard financial statements;
• Should be influential at least across peers, have understanding of the whole RA framework, and be able to communicate clearly to levels above;
•  Attention to detail, urgency and advanced analytical skills.

Must have technical / professional qualifications

•  At least a BSc Degree in either Computer Science, Information Systems, Statistics or equivalent;
• Proficient in PL/SQL and SQL in different DBMAs such as MYSQL, SQL Server, Oracle, Access, Excel. Understanding of the ETL Process;
• Proficient in one of the Business Intelligence Tools such as Business Objects, Tableau, SAP Lumira, Qlik Sense etc;
•  Proficient in one of the “machine learning” languages such as Python, R, Cypher and graph databases such as Neo4J

Key performance indicators

• M-Pesa financial reconciliations culminated by the ultimate reconciliation of the Trust Fund and all internal financial accounts;
• Adoption of Machine Learning and/or Artificial Intelligence for advanced data analytics with at least two new use cases;
•  Monthly business reports to Management on revenue leakages and prevented as well as the state of the Finance Digital journey.