Job description

Roles and Responsibilities: 

• Provide high-quality analysis (through tools including SQL, statistical software, Excel, PowerBi, and computer science models) to inform management on credit performance of the portfolio, products and customers.
• Contribute to the development of reports to key stakeholders including senior management, the board of directors and investors, including graphical analysis, PowerPoint presentations, and verbal and written communications.
• Design and implement experiments/initiatives geared towards improving and maintaining a healthy credit performance across M-KOPA’s customer base, this includes but not limited to performing statistical and quantitative analyses on datasets to identify root causes of observed risk trends
• Work on the entire product development lifecycle from ideas generation, design, development, and validation, leading up to launch
• Contribute to the development, documentation and maintenance of credit and financial models to be used by the business, such models include loss forecasting, Probability of Default, Exposure at Default, and Loss Given Default models among other models
• Monitor and report on key performance metrics on M-KOPA’s core products as well as the development of new tools and capabilities to perform portfolio construction or analytics independently, including the use of statistical and machine learning techniques
• Execute work in coordination with other departments regarding credit-related communications
• Collaborate with the Data/Tech Team to improve data accuracy and reliability for reporting

Ideal Candidate Profile:

• Strong data or financial analytical skills to effectively review and report on credit performance metrics
• Interpersonal skills to effectively communicate with and manage business expectations with key stakeholders
• A positive, learning-oriented attitude and capacity for self-empowerment
• Possession of a University degree preferably in a quantitative field such as Economics/Econometrics, Engineering, Mathematics, Computer Science or Finance (Financial Engineering, Finance Theory, or Computational Finance) or an equivalent combination of education and work-related experience
• At least two years of strong quantitative experience with loss forecasting, default management and credit risk modelling to include models that produce Probability of Default, Exposure at Default, and Loss Given Default
• Advanced knowledge and demonstrated proficiency of data analysis in at least one programming language (Python, Matlab, R, Ruby, C# or C++) in addition to skills to develop analysis queries and procedures in SQL or other business intelligence and analysis software applications for data segmentation, clustering, time series analysis, aggregation, and statistics
• Knowledge of lending business practices and products preferred
• Excellent documentation, projects management, oral and written communication and presentation skills including the ability to distil complex ideas into simple explanations
• Previous experience in finance, business intelligence or consumer credit analysis preferred.
• Proficiency in Excel, PowerPoint, Word, and sound understanding of statistics and quantitative methods