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At M-KOPA, our aim is to increase access to life-improving technologies at huge scale. We do this through an innovative credit model – pay-as-you-go asset financing – of which M-KOPA was an early global pioneer. With offices in Nairobi, Kampala, Lagos, and London, M-KOPA serves over 1 million low-income households in Sub-Saharan Africa. Since its commercial launch in 2012, M-KOPA has made its name in off-grid solar power, providing customers with solar panels and solar-powered lights, televisions, radios, fridges, and more – this is often our customers’ first access to electricity.
M-KOPA’s affordable credit model can also be applied to assets beyond off-grid solar power, and in 2019, we began providing credit for smartphones, which enables our customers to move from feature phones to smartphones and improve their connectivity, communication, and information access. Today, smartphone financing is a rapidly growing business line – with enormous opportunities for innovation and increasing our customer impact.
M-KOPA currently employs over 1,000 full-time staff across its operating countries. We value progress, innovation, pragmatism, collaboration, and – most of all – our customers. We have been well recognised for our pioneering business model and scale.
- Lead analysis, management, and communications regarding credit performance of the company’s portfolio, customers, and products and services. This includes managing multi-source data analysis, designing experiments, testing hypotheses, and compiling presentations and reports used internally and by external stakeholders. The objective of the role is to provide actionable insights to understand and influence consumer credit behavior.
- The role is akin to an analytical project manager, bridging credit experience, qualitative observations, economic and behavioral research, and technical data analytics to answer key questions about M-KOPA’s credit portfolio. This role requires an ability to clearly identify a problem, scope an approach to understanding the problem, manage analytical workflow to answer the questions at hand, and clearly communicate actionable recommendations.
NOTE: The role is a global role, with a preference for experience in Kenya, Uganda, and/or Nigeria
Key job functions
- Provide quality analysis (typically provided via SQL, R, Python, Excel, and BI visualization tools) to inform management on the credit performance of the portfolio, products, and customers. This includes regular portfolio and product-level reporting as well as managing ad-hoc investigations and causal diagnoses.
- Design and implement initiatives and experiments geared towards improving and maintaining healthy credit performance across M-KOPA’s customer base. This includes working extensively with other departments.
- Contribute to the development of credit and financial models to be used by the business, including but not limited to IFRS 9 provisioning and bad debt modeling, cash flow modeling, and predictive loss rate models
- Lead the development of reports to key stakeholders including senior management, board of directors, and investors, utilizing graphical analysis, Powerpoint presentations, and verbal and written communications.
- Monitor and report on key performance metrics on M-KOPA’s core products and pilots, including standard and non-standard forms of portfolio health and delinquency reporting, repayment rates, roll rates, etc.
Experience, skills and competencies
- 6-10 years of work experience in an analytical field such as consumer credit, asset finance, pricing, data science, behavioral research, or strategy consulting, including experience managing teams, portfolios, and projects
- Credit, data, and financial analysis skills to effectively evaluate and report on key performance metrics
- Knowledge of lending business practices and consumer credit in emerging markets strongly preferred.
- Strong interpersonal and presentation skills to effectively communicate with colleagues and senior stakeholders
- Understanding of business concepts including ROI analysis, discounted cash flow, causality, & statistical significance
- Bachelors or Masters degree preferably in a quantitative field, including economics, econometrics, data analytics, computer science, statistics, engineering, credit management, finance, or behavioral psychology
- Proficiency in structuring analytical projects and familiarity with tools including SQL, R!, Python, PowerBI, Excel, PowerPoint, Word, as well as a clear understanding of statistics and quantitative methods and best practices
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