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Listed on the Johannesburg Stock Exchange (JSE) and the Namibian Stock Exchange (NSX), FirstRand Limited is one of the largest financial institutions in Africa. FirstRand’s vision is to be the African financial services group of choice, create long-term franchise value, deliver superior and sustainable economic returns to its shareholders within acc...
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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.
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: 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
Closing Date:18th, March 2022
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Purpose
To investigate and handle any errors or incidents that are raised or reported against the programmed functionality of the Banks’ financial processes, systems and ledgers. Amongst others, errors and incidents may relate to financial balancing and reconciliations, journal processing controls, data integrity and warehousing, financial reporting or fraud prevention.
Experience and Qualifications
- Relevant undergraduate degree in Finance / IT / Accounting.
- 0-2 years working experience.
- Advanced computer skills.
- Practical knowledge of database management applications (e.g. SQL) and relevant reconciliation tools will be an advantage.
Closing Date:18th, March 2022
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Purpose
To build, optimise and implement innovative quantitative analytical methodologies, procedures, and advanced mathematical models that provide analytical support and interpret insights, to address business opportunities and problems and implement business strategy, under guidance against predicted results and deliver according to set processes and procedures
Experience and Qualifications
- Minimum Qualification - Relevant Degree in Maths, Stats, Engineering, Computer Science, Econometrics, Physics or Actuarial Science
- Experience - 1 to 3 years’ experience in data environment
- Additional Knowledge - Domain knowledge with regards to financial services: Credit, Pricing, Marketing, CVM, Trading etc.
- Design thinking
- Analytics Ops, Agile and SAFe concepts will assist
- 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
- 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#/Java, .NET or VBA, Excel
- Calculus (including differential, integral and stochastic)
- Linear algebra and differential equations
- 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
Closing Date:18th, March 2022
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Purpose
- To provide a specialist business solution and design, coordinate and implement the solution across the business.
Experience and Qualifications
- Minimum Qualification - Relevant Degree
- Preferred Qualification - Relevant Post Graduate Business or IT, Diploma in BA or Certified Professional Business Analyst (CBAP)
- Experience - 5 to 8 years experience in a similar environment, of which 2 to 3 years ideally at management level
Closing Date:18th, March 2022
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Purpose
To design, develop, implement and maintain scalable and robust data integration interfaces and data models required by Analysts, Product Managers and Data Scientists.
Experience and Qualifications
- Relevant BSC Degree in Computer Science or similar tertiary qualification in the Data Management field.
- 6+ years extensive experience with designing and building data warehouses, BI systems and complex data eco systems.
Closing Date:15th, March 2022
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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
Closing Date:18th, March 2022
go to method of application »
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
Closing Date: 25th, March 2022
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Purpose
To implement the Analytics standards across big complex business areas, that contribute to the monetisation of data through the development and delivery of advanced mathematical models and business principles that find hidden patterns and associations in data used to influence business strategy, inform channel design and make predictions on the behaviour of our clients
Experience and Qualifications
- Minimum Qualification - Relevant undergraduate degree
- Preferred Qualification - Relevant post graduate degree or recognised Information Management and/or Data science certification
- Experience - 5-8 years relevant experience in information management/data science/Data engineering/Computer Science of which 3-4 years ideally at senior management
Closing Date: 21th, March 2022
go to method of application »
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.
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: 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
Closing Date: 22nd, March 2022
go to method of application »
Purpose
To provide expertise, advice and support through the implementation of the organisational information management strategy by facilitating the definition, design and implementation of information management processes, business and technical requirements and solutions. Information management encompasses information architecture management, metadata management, master and reference data management, data development management, business intelligence and data warehousing management, content, document and records management, data quality management, data storage and operations management and information security and data privacy management.
Experience and Qualifications
- Minimum Qualification - Relevant BSc or BCom degree
- Preferred Qualification - Honours degree with focus in Information Systems
- Experience - 2 to 5 years related experience
Closing Date: 18th, March 2022
Method of Application
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