Requirements

• 3–6+ years of experience in Business Intelligence, Data Analytics, or similar role (preferably in fintech, banking, or lending).
  
• Strong proficiency in SQL (mandatory) and experience with Python or R (preferred).
  
• Experience with BI tools (e.g., Power BI, Tableau, Looker).
  
• Strong understanding of lending metrics (PAR, NPL, roll rates, recovery rates).
  
• Ability to translate data into clear business insights and recommendations.
  
• Experience working with large, complex datasets.
  

1. Data Analysis & Insight Generation

• Analyze large datasets across the lending lifecycle (acquisition, underwriting, disbursement, repayment, collections, recovery).
  
• Identify trends, risks, and opportunities to improve portfolio performance.
  
• Deliver actionable insights to Credit, Operations, Product, and Leadership teams.
  

2. Dashboarding & Reporting

• Build and maintain real-time dashboards (e.g., PAR, NPLs, recovery rates, disbursement volumes).
  
• Automate recurring reports for daily, weekly, and monthly performance tracking.
  
• Ensure data accuracy, consistency, and accessibility across teams.
  

3. Credit & Risk Analytics

• Support development and monitoring of credit scoring models using alternative data (telco, behavioral, banking, device data).
  
• Track portfolio health metrics (PAR 30/90, roll rates, default rates).
  
• Conduct cohort analysis to evaluate loan performance and risk segmentation.
  

4. Collections & Recovery Analytics

• Analyze repayment behavior and optimize collections strategies.
  
• Build segmentation models for early-stage, late-stage, and high-risk borrowers.
  

• Support skip tracing and recovery optimization using data insights, including escalation effectiveness.
  

5. Product & Growth Analytics

• Partner with Product teams to track user journeys, conversion funnels, and drop-off points.
  
• Design and evaluate A/B tests to improve acquisition, engagement, and repayment rates.
  
• Provide insights to optimize pricing, loan offers, and customer targeting.
  

6. Process Automation & Data Infrastructure

• Work with Data Engineering to improve data pipelines, ETL processes, and warehouse structures.
  
• Automate manual reporting processes using SQL, Python, or BI tools.
  
• Ensure data governance and best practices in analytics.
  

7. Regulatory & Compliance Reporting

• Support reporting requirements aligned with Central Bank of Nigeria (CBN) guidelines.
  
• Ensure integrity of financial and risk data used for audits and regulatory submissions.