Business Intelligence Analyst

FairMoney is a pioneering mobile banking institution specializing in extending credit to emerging markets. Established in 2017, the company currently operates primarily within Nigeria, and it has secured nearly €50 million in funding from renowned global investors, including Tiger Global, DST, and Flourish Ventures. In alignment with its vision, FairMoney is actively constructing the foremost mobile banking platform and point-of-sale (POS) solution tailored for emerging markets. The journey began with the introduction of a digital microcredit application exclusively available on Android and iOS devices. Today, FairMoney has significantly expanded its range of services, encompassing a comprehensive suite of financial products, such as current accounts, savings accounts, debit cards, and state-of-the-art POS solutions designed to meet the needs of both merchants and agents. FairMoney thrives on its diverse workforce, bringing together talent from over 27 nationalities. This multicultural team drives the company’s mission of reshaping financial services for underserved communities. To gain deeper insights into FairMoney’s pivotal role in reshaping Africa’s financial landscape, we invite you to watch an informative video . Role Description – Business Intelligence Analyst We are looking for a Business Intelligence Analyst to turn collections and lending data into clear, decision-ready insight. You will own the reporting layer that sits between our raw data and our operational and executive stakeholders, building dashboards and analyses that drive recovery performance across our portfolio. This is a hands-on role for someone who is equally comfortable writing complex SQL and presenting a clean executive dashboard. Roles and Responsibilities Design, build, and maintain BigQuery data models and queries supporting collections, recovery, and portfolio reporting. Develop and maintain Tableau dashboards covering DPD buckets, roll rates, RPC/PTP performance, recovery rates, campaign performance, and agent/team productivity. Partner with collections operations, finance, and leadership to translate business questions into scalable data products. Build and automate recurring reporting (daily, fortnightly, monthly) and reduce manual reporting effort. Investigate data quality issues, reconcile discrepancies across source systems (dialer, CRM, core banking, ticketing), and ensure metric definitions are consistent and trusted. Monitor KPIs against targets, flag anomalies, and surface the “why” behind trends rather than just the numbers. Support experiments and initiatives (e.g. cashback, campaign migrations, channel mix) with measurement frameworks and impact analysis. • 8+ years in a BI, data analyst, or analytics engineering role, ideally within an NBFC, microfinance bank, fintech lender, or banking environment. • Strong, demonstrable SQL skills on Google BigQuery (CTEs, window functions, partitioning, query optimization, cost awareness). • Proven expertise building production dashboards in Tableau (LODs, calculated fields, parameters, performance tuning). • Solid understanding of the collections and lending lifecycle: DPD buckets, roll rates, recovery and resolution metrics, PTP/RPC, write-offs, and portfolio risk. • Ability to communicate findings clearly to both operational teams and senior leadership. Nice to Haves • Experience with dialer systems, CRM/ticketing platforms, and core banking or loan management systems. • Familiarity with Metabase or other BI tools, and with cloud data warehousing concepts. • Exposure to multi-market operations and the data complexity that comes with it. • Awareness of data protection and governance requirements in financial services. What Success Looks Like Within the first 30 days, you will have taken ownership of core collections dashboards, established trusted metric definitions, and delivered at least one piece of analysis that meaningfully informs recovery strategy. Private Health Insurance Pension Plan Paid Time Off Work From Home Training & Development Recruitment Process A screening interview with one of the members of the Talent Acquisition team for 30 minutes. Technical interview with Dialer Administrator Team Lead 45-60 minutes. Final interview with Dialer Manager for 45-60 minutes.