Purpose Statement
Delivering business solutions via a collaborative approach involving mathematical formulae, business tactics, technological applications and behavioural sciences to help senior management make data driven decisions.

Experience

3 years relevant experience in statistical analysis
Experience must include the following (within the Retail Credit Risk Management Environment):
- Extracting and Aggregating Data from Large Relational Databases
- Data Mining and Predictive Modelling

Qualifications (Minimum)

Honours Degree in Data Science or Mathematics

Qualifications (Ideal or Preferred)

Masters Degree in Data Science or Mathematics

Knowledge

Analytics
Predictive Modelling and Machine Learning
Project management methodologies
IT implementation cycle
Credit cycle
Technical understanding and knowledge (different operating systems / databases /programming languages)
General business acumen to identify the impact technical issues may have on design and delivery of solutions.
Best practices and tools in credit risk
Interpretation of user requirements and translation into business requirements specifications
Retail credit environment / industry
Confidentiality and intellectual property implications and constraints
Interpretation of user requirements
Translation of business requirements into business requirement specifications

Skills