Data Analyst
Data Analyst
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Job Description
Job Summary
Own the analytics backbone for Personal Banking (Digital Savings & USSD) Business Banking Agent (SSA/SA & POS/MPOS) Business Banking- Micro & Small & Business Banking- Medium & Large. Deliver timely accurate and actionable insights that grow users and agents improve POS uptime optimize campaigns and reduce risk. Uphold data privacy CBN/NDPR compliance and strong governance across all datasets.
Key Responsibilities
Personal Banking (Digital Savings & USSD)
- Track daily/weekly/monthly app & USSD usage (MTU DUM registrations activations deposits/user churn).
- Segment customer behavior by LGA cohort and product usage; identify drop-offs and reactivation opportunities.
- Measure campaign impact (CAC LTV ROI) by channel; recommend budget shifts based on performance.
- Monitor VAS (airtime data bills) and drive cross-sell/up-sell insights and experiments.
Business Banking -Agent (SSA/SA & POS Network)
- Maintain LGA-level agent allocation and activation dashboards; track device allocation vs. active usage.
- Analyze agent performance (Txn volume/value deposits retention) flag outliers and recommend actions.
- Publish weekly network health (uptime % repair TAT inactive devices) and follow through on fixes.
Business Banking- Medium & Large
- Track and analyze Corporate Internet Banking usage (MTU DUM registrations activations deposits/user churn).
- Segment customers by LGA industry and usage patterns; identify drop-offs and reactivation triggers.
- Monitor VAS adoption and develop cross-sell/up-sell strategies.
Cross-Business & Strategic Analytics
- Partner with Relationship Managers Product and Marketing to turn insights into action.
- Maintain integrated Executive Dashboard for MD & Board blending Personal and Business Banking KPIs.
- Run daily/weekly/monthly reporting calendar; manage distribution lists and archive for auditability.
- Support risk monitoring: detect anomalies reversals and KYC exceptions; partner with Compliance on actions.
- Own data quality processes (QA checks reconciliations) and data dictionaries across reporting assets.
- Drive automation to reduce manual effort (SQL/Python jobs scheduled extracts parameterized dashboards).
Requirements
Required Skills & Experience
- Bachelor s degree in Statistics Economics Data Science Computer Science or related discipline
- 3 4 years in analytics within fintech/banking/telco; strong commercial orientation
- Advanced SQL and Power BI; proficient Excel; Python for automation and deeper analysis
- Fluency with fintech KPIs (CAC LTV ARPU churn MTU/DUM) cohort & funnel analysis
- Experience with app databases USSD logs POS/MPOS feeds CRM/marketing platforms
- Strong data hygiene (QA reconciliation) documentation and stakeholder communication
Benefits
Employment Type
Full Time
