An opportunity to be a part of the end to end model lifecycle that enables senior management to make informed data-driven decisions.
Drive business solutions through technical and predictive modelling, collaboration with professionals with diverse skillsets, as well as stakeholder- and business engagement.
Experience & Qualification
Relevant Honours Degree with a major in Data Science / Mathematics / Statistics / Risk Management with 4 - 6 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
Predictive Modelling and Machine Learning
Project management methodologies
IT implementation 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
Numerical Reasoning skills
Computer Literacy (MS Word, MS Excel, MS Outlook)
Attention to Detail
Interpersonal & Relationship management Skills
Commercial Thinking Skills