As a Risk Analytics Engineer you are the critical bridge between advanced analytics and our production environment. You will be embedded within a cross-functional squad responsible for the operationalization of risk models and strategies. Your primary mission is to ensure that the analytical solutions built by our data scientists and risk analystsfrom credit scorecards to real-time fraud modelsare deployed monitored and managed in a robust automated and scalable fashion. You will build and own the MLOps pipelines and solutions that bring our risk intelligence to life.
Qualifications :
Qualification:
- Completed Matric
- Bachelors degree in Computer Science Software Engineering Information Systems or a related quantitative field.
Experience Required
- 5-7 years experience in building databases warehouses reporting and data integration solutions.
- Experience building and optimising big data data-pipelines architectures and data sets. Experience in creating and integrating APIs.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- 8-10 years deep understanding of data pipelining and performance optimisation data principles how data fits in an organisation including customers products and transactional information. Knowledge of integration patterns styles protocols and systems theory
- 8-10 years experience in database programming languages including SQL PL/SQL SPARK and or appropriate data tooling. Experience with data pipeline and workflow management tools
Additional Information :
Behavioural Competencies:
- Adopting Practical Approaches
- Articulating Information
- Checking Things
- Examining Information
- Interpreting Data
- Managing Tasks
- Producing Output
Technical Competencies:
- Big Data Frameworks and Tools
- Data Engineering
- Data Integrity
- Data Quality
- IT Knowledge
- Stakeholder Management (IT)
Remote Work :
No
Employment Type :
Full-time
As a Risk Analytics Engineer you are the critical bridge between advanced analytics and our production environment. You will be embedded within a cross-functional squad responsible for the operationalization of risk models and strategies. Your primary mission is to ensure that the analytical solutio...
As a Risk Analytics Engineer you are the critical bridge between advanced analytics and our production environment. You will be embedded within a cross-functional squad responsible for the operationalization of risk models and strategies. Your primary mission is to ensure that the analytical solutions built by our data scientists and risk analystsfrom credit scorecards to real-time fraud modelsare deployed monitored and managed in a robust automated and scalable fashion. You will build and own the MLOps pipelines and solutions that bring our risk intelligence to life.
Qualifications :
Qualification:
- Completed Matric
- Bachelors degree in Computer Science Software Engineering Information Systems or a related quantitative field.
Experience Required
- 5-7 years experience in building databases warehouses reporting and data integration solutions.
- Experience building and optimising big data data-pipelines architectures and data sets. Experience in creating and integrating APIs.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- 8-10 years deep understanding of data pipelining and performance optimisation data principles how data fits in an organisation including customers products and transactional information. Knowledge of integration patterns styles protocols and systems theory
- 8-10 years experience in database programming languages including SQL PL/SQL SPARK and or appropriate data tooling. Experience with data pipeline and workflow management tools
Additional Information :
Behavioural Competencies:
- Adopting Practical Approaches
- Articulating Information
- Checking Things
- Examining Information
- Interpreting Data
- Managing Tasks
- Producing Output
Technical Competencies:
- Big Data Frameworks and Tools
- Data Engineering
- Data Integrity
- Data Quality
- IT Knowledge
- Stakeholder Management (IT)
Remote Work :
No
Employment Type :
Full-time
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