about us
make a promise
be deeply invested
value our differences
build trust, not territory
have courage
always do the right thing
stay curious and you have one simple goal : to improve the lives of customers through simple, effective solutions that meet their needs, contact us today and join a winning team.
All appointments will be made in line with the Bank’s Employment Equity plan The Bank supports the recruitment and advancement of individuals with disabilities.
In order for us to fulfill this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.
purpose
To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced mathematical models that provide analytical support and interpret insights, using advanced analytics technologies, to address business opportunities and problems and implement business strategy.
experience and qualifications
Minimum Qualification - B Degree Maths, Stats, Engineering, Computer Science, Econometrics, Physics or Actuarial Science
Preferred Qualification - Honours Degree
Experience - 3 - 5 years’ experience in a data environment, of which 1 - 2 years ideally at a at junior (entry level) management level
Additional Knowledge - Deep domain knowledge with regards to financial services : Credit, Pricing, Marketing, CVM, Trading etc.
Design thinking
Analytics Ops, Agile and SAFe concepts will assist
Concepts such as : Exploratory data analysis, Data Science Pipeline lines
Hands on experience using model such as : Naïve Bayes, Support Vector Machines, Classifications, Boosting Algorithms, Time Series, Feature Engineering and
Dimensionality Reduction
Data and Information Management topics e.g. structure, dimensions, storage
Object-oriented programming
Big data modelling
Database management
Python, SQL, MATLAB, SAS, S-PLUS or R (used for statistical analysis)
Monte Carlo techniques
Machine learning
Data mining and data modelling
C++ (used for high-frequency trading applications)
Scala and Spark
C# / Java, .NET or VBA, Excel
Mathematical skills
Calculus (including differential, integral and stochastic)
Linear algebra and differential equations
Numerical linear algebra
Probability and statistics
Game theory
Portfolio theory
Equity and interest rate derivatives, including exotics
Systematic and discretionary trading practices
Credit-risk products
Financial modelling
Data visualisation and reporting 
