Lead Auditor, Data and Analytics (Group Internal Audit)

About this role

Flutterwave is recruiting for a Lead Auditor, Data & Analytics within Group Internal Audit. The role combines audit and data engineering to design data pipelines, monitoring agents, and a live Assurance Dashboard to review transactions, surface exceptions, and demonstrate business value. It aims to create an AI-native internal audit function for payments and banking operations, focusing on continuous monitoring and automation while auditors concentrate on judgment and investigation. The role involves collaborating with multiple business and tech teams to enable continuous assurance and maintain independence between monitoring and remediation. Location is Lekki, Lagos, Nigeria, with reporting to the Head of Internal Audit and management.

What you would do

• Build and operate AI-powered monitoring agents across high-value use cases (settlements, reconciliations, revenue assurance, API integrity, vendor spend, privileged access).
• Develop and maintain the live Assurance Dashboard showing risks, revenue leakage, findings, remediation status, fraud trends, control failures and financial exposure.
• Design and deliver the data layer for continuous assurance with production data access secured for auditing and analytics teams.
• Own data quality and governance, ensuring data protection, privacy and residency requirements in pipelines and agents.
• Assess data quality, completeness and lineage; establish data ownership with business and technology teams.
• Maintain a model and agent inventory with documented logic, testing results, accuracy and false-positive rates; ensure AI governance and responsible-AI standards.
• Translate findings into measurable business value and report progress weekly to Head of Internal Audit and management.
• Baseline and track outcome KPIs such as revenue leakage identified, costs eliminated, losses prevented, and automation of manual controls.
• Translate analytics results into clear exceptions for auditors and management action.
• Collaborate with cross-functional teams to build the function's data and AI capability and support the operating model separating monitoring from remediation.

What they are asking for

• 7+ years building data pipelines, analytics or automation in financial services, payments, fintech or similar data-driven environment.
• Hands-on experience building anomaly detection, reconciliation or monitoring solutions on large transaction datasets.
• Bachelor's degree in a relevant field (e.g., Data Science, Computer Science, Engineering, Statistics, Finance, Accounting, Information Systems).
• Strong SQL and Python (or equivalent) and experience with modern data stacks (cloud data warehouses, orchestration tools, BI/dashboard platforms).
• Practical experience applying AI or LLM-based tools to real business problems, including testing and validation.
• Experience in internal audit, risk, fraud or revenue assurance analytics.
• Preferred: exposure to payments, settlement, treasury or banking data; relevant certifications (CISA, CIA, CFE) or cloud/data engineering credentials; familiarity with ICFR, regulatory reporting or data protection regulations.

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