The successful candidate will lead developments on Credit Risk Management for micro-finance being guided and supported by the Big Data & Analytics Director. He/she will develop credit risk models and algorithms based on large volumes of data, and deploy them to manage portfolios of large number of micro-loans with the aim to maximize adoption and revenues.
The candidate will be able to demonstrate his/her expertise on models and data, high level of business understanding, critical thinking, personal skills, and knowledge transfer capabilities. He/she will have the opportunity to further develop his/her knowledge on credit risk, portfolio management and machine learning.
- Design, develop and implement scorecards for micro-finance.
- Develop and deploy advanced credit risk models and algorithms.
- Manage large portfolios of micro-loans through financial and mathematical modelling.
- Transfer knowledge on credit risk model development and management.
- Analyze large data volumes to identify credit risk factors.
- Develop strategies for credit risk management and revenue maximization
- BSc and MSc in Mathematical Sciences, Computer Science or Finance from an accredited institution.
- Minimum of 3 years’ experience in a related role (e.g. credit risk analyst/manager and/or data scientist).
- Strong analytical skills, evidence of statistical/machine learning models and algorithms development.
- Hands-on experience at least in two of the following (with descending significance):
- Credit scorecard development and implementation
- Credit portfolio management
- Machine learning
- Risk analytics
- Big data credit scoring
- Ability to set-up, organize and monitor pilots for testing and comparing risk models
- Experience in and ability to gain risk insights analyzing large volumes of data.
- Strong interpersonal and communication skills.
- Ability to hit tight deadlines and work under pressure and strict attention to detail.
- Excellent judgment and problem-solving skills.
The following will be considered a plus
- PhD in Mathematical Sciences, Computer Science or Finance from an accredited institution.
- Hands-on experience of big data processing and analytics.
- Creative skills.
- Programming skills.