FairMoney
Financial Services
Description
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.
Responsibilities
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.
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