The successful Data Scientist will be responsible for developing cutting edge credit risk models over big data. He/she will work closely with the Big Data and Analytics Director and the rest of the team to develop advanced credit-risk models and algorithms for nano- and micro-finance.
Working closely with other creative minds, the candidate will be able to demonstrate his/her expertise on data, models and machine learning, as well as his/her high level of analytical and creative skills. He/she will have the opportunity to further develop knowledge and expertise on AI, machine learning, predictive and risk analytics.
- Design and implement credit risk models and algorithms beyond the state of the art.
- Develop and deploy advanced profit scoring models.
- Identify credit risk factors by applying computational methods to large data volumes.
- Apply deep and ensemble learning to optimize risk models.
- Determine optimal risk strategies through computational means.
- Deliver credit-risk insights through big data risk analytics.
Qualifications & Skills
- BSc and MSc in Mathematical Sciences or Computer Science from an accredited institution.
- Hands-on experience at least in two of the following (with descending significance):
- Machine learning and AI
- Credit risk models
- Big-Data; Apache SPARK
- Risk Analytics
- Predictive Analytics
- Mathematical & Statistical modelling
- Ability to efficiently search and understand the scientific literature of mathematical models, machine learning and AI.
- Ability to judge the relevance of existing models and algorithms to specific business needs.
- Strong analytical skills.
- Excellent judgment and problem-solving skills.
- Passion for learning, exploring and developing new models and machine learning and AI algorithms.
- Ability to hit tight deadlines and work under pressure and strict attention to detail.
Will be considered a plus.
- PhD in Computer Science, Mathematical Sciences or Finance from an accredited institution.
- Hands-on experience of big data processing and analytics.
- Hands-on experience of data bases (SQL and NoSQL).
- Communication skills.
- Creative skills.
- Programming skills.
- Hands-on experience of Java.