Purpose Statement
To solve business problems, create new products and services, and improve processes through using the disciplines of data science, quantitative (financial) analysis, and traditional scoring techniques - translating active business data into usable strategic information.
To look at ways of analysing and optimising data as it relates to a specific business area; framing data analysis in terms of the decision-making process for questions or business problems posed by a stakeholder.
To help build and deliver Capitec's AI strategy, enabling data-led and improved business decision making.
To design quantitative advanced analytics models that answer business questions and/or discover opportunities for improvement, increased revenue, or reduced costs.
Education (Minimum)
Honours Degree in Mathematics or Statistics
Education (Ideal or Preferred)
Masters Degree in Mathematics or Statistics
Experience and Knowledge
Minimum Experience and Knowledge:
Length of experience required is also conditional on qualifications obtained
Statistical (predictive and classification) model development and deployment principles and techniques; including traditional scoring (logistic regression with binning and missing value replacement, e.g., reject inference), Machine Learning (neural networks, SVM, random forests, etc.), and quantitative analysis (time value of money, etc.)
At least one Machine Learning language (e.g., Python or SAS Viya)
Business analysis and requirements gathering
General business know-how (e.g., risk, compliance, operations - such as NCR, POPIA, and SARB)
Cloud environments (e.g., Azure, AWS, and large relational databases)
Functional business area (e.g., Credit) environment knowledge and experience
Developing scorecards from scratch
Underlying theory and application of machine learning models
Best practices for decision science (such as reusability, reproducibility, continuous monitoring, etc.)
Ideal Experience and Knowledge:
Over 5 years' experience in an analytical science role
Working with multiple teams to deliver predictive models into a production environment
Financial sector
Credit environment / industry (Credit cycle)
Bank decision science lifecycle
Skills
Numerical Reasoning skills
Researching skills
Analytical Skills
Problem solving skills
Decision making skills
Planning, organising and coordination skills
Attention to Detail
Presentation Skills
Interpersonal & Relationship management Skills
Communications Skills