About the position
FNB International Global Business Banking is looking for a Quantitative Analyst III to support the business unit in the Rest of Africa space from an analytics perspective.
Role 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.
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
- Develop and implement advanced statistical models and data analysis to optimise processes, inform strategic decisions and meet current and future business requirements, reduce risk and generate profits
- Deliver value add outputs across the analytics value chain in delivery of business strategy
- Implement localised Analytics strategy to address business needs
- Utilise advanced analytics technologies, program own statistical model and apply advanced data modelling methodologies that inform future fit strategic decisions and test current assumptions
- Develop, encourage and nurture collaborative relationships within FNB and/or across the FRG
- 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
- Contribute to the development of a budget aligned to operational delivery plans, monitor effectiveness and report on variances.
- 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:
- The successful candidate must understand financial resource management initiatives and product development
- The successful applicant will run with analytics associated with product development
- Building credit and none credit models (Scorecards, attrition and propensity models)
- Must understand a platform business
- SAS and SQL are none negotiable
Qualification and Experience:
- inimum Qualification - B Degree Maths, Stats, Engineering, Computer Science, Econometrics, Physics or Actuarial Science
- Preferred Qualification - Honours Degree
- Experience - 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
Desired Skills:
- SAS
- SQL
- Data Analysis
- Python
- Statistical modelling
- Data Mining
Desired Work Experience:
Desired Qualification Level:
