purpose

To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced mathematical models that provide analytical support and interpret insights, to address business opportunities and problems and implement business strategy, with minimal guidance.

responsibilities

• Prevent wastage and identify process improvements to contain and reduce costs
• Assess own performance through seeking timely, and clear feedback and request training where appropriate
• Utilise, refine and enhance advanced statistical models and data analysis to inform decision making and address business needs
• Contribute to creative business solutions, optimisation of processes and conduct statistical modelling and data analysis to inform strategic decisions, under limited supervision
• Assist in the delivery of value-add outputs across the analytics value chain in delivery of business strategy
• Implement localised Analytics strategy to address business needs, under limited supervision
• Develop new insights into situations and apply innovative solutions to make organisational improvements
• Focus on providing optimal services and improving service delivery processes to meet or exceed customer expectations
• Develop, encourage and nurture collaborative relationships within FNB and/or across the FRG
• Ensure compliance to legislative and audit requirements and adherence to relevant processes
• Build working relationships across teams and functional lines to enhance work delivery, collaboration and innovation

additional requirements

In accordance with National Credit Act (NCA) candidates applying for this role will require a credit record check.

experience and qualifications

• Minimum Qualification – Relevant Degree in 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 junior specialist 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: Na¥ve 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