Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
Scoutfield Logo

See all jobs on Scoutfield

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
FairMoney

Business Intelligence Analyst

FairMoney

. Analyze large datasets across the lending lifecycle, including acquisition, underwriting, disbursement, repayment, collections, and recovery .

Posted 9/29/2026full-timeLagos • NigeriaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data analysis and visualization, with a strong focus on lending metrics and performance optimization. Proficient in SQL and experienced in using BI tools to deliver actionable insights and support data-driven decision-making.

Highest-signal resume keywords
SQL ProficiencyData AnalysisDashboard DevelopmentCredit AnalyticsA/B Testing

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Data AnalysisDashboard DevelopmentCredit AnalyticsA/B TestingData StorytellingPerformance ReportingSegmentation ModelingRisk SegmentationData AutomationCohort Analysis
Soft Skills
Problem-SolvingCritical ThinkingStakeholder Communication
Tools & Technologies
SQLPythonRPower BITableauLooker
Industry Keywords
Lending LifecyclePortfolio PerformanceData GovernanceFinancial Data IntegrityCentral Bank Compliance

Tech Stack

Tools & technologies
ETLPythonSQLTableau

About the role

Key responsibilities & impact
  • Analyze large datasets across the lending lifecycle, including acquisition, underwriting, disbursement, repayment, collections, and recovery
  • Identify trends, risks, and opportunities to improve portfolio performance
  • Deliver actionable insights to Credit, Operations, Product, and Leadership teams
  • Build and maintain real-time dashboards tracking PAR, NPLs, recovery rates, and disbursement volumes
  • Automate recurring daily, weekly, and monthly performance reports
  • Ensure data accuracy, consistency, and accessibility across teams
  • Support development and monitoring of credit scoring models using telco, behavioral, banking, and device data
  • Track portfolio health metrics, including PAR 30/90, roll rates, and default rates
  • Conduct cohort analysis to evaluate loan performance and risk segmentation
  • 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
  • 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
  • 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 analytics best practices
  • Support reporting requirements aligned with Central Bank of Nigeria guidelines
  • Ensure integrity of financial and risk data used for audits and regulatory submissions
  • Success metrics include accurate and timely reporting, improved portfolio performance, increased collections efficiency, faster decision-making through real-time dashboards, and measurable impact of data-driven experiments
  • First six months: deliver functional lending and collections dashboards, reduce defaults and improve recovery rates, automate reporting, collaborate with Credit, Operations, and Product teams, and influence business decisions through data-driven recommendations

Requirements

What you’ll need
  • 5+ years of experience in Business Intelligence, Data Analytics, or a similar role, preferably in fintech, banking, or lending
  • Strong proficiency in SQL (mandatory)
  • Experience with Python or R (preferred)
  • Experience with BI tools such as Power BI, Tableau, or Looker
  • Strong understanding of lending metrics, including PAR, NPL, roll rates, and recovery rates
  • Ability to translate data into clear business insights and recommendations
  • Experience working with large, complex datasets
  • Data analysis and storytelling
  • Dashboard development and visualization
  • Credit and risk analytics
  • Experimentation and A/B testing
  • Problem-solving and critical thinking
  • Stakeholder communication

Benefits

Comp & perks
  • Private Health Insurance
  • Pension Plan
  • Training & Development
  • Performance Bonus