Job SummaryOwn 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 ResponsibilitiesPersonal 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). RequirementsRequired 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 BenefitsIndustry Standard
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