Perform the required data exploration activities needed to set proper data elements definitions used in the process of creating information and analytics using machine learning, data mining, and information quality techniques in order to set proper data elements definitions used in the process of creating information and analytics.

2. Identify information quality defects patterns and trends and perform root-cause analysis, gap analysis, and impact analysis to solve complex business problems.

3. Generate Information Quality analytical monitoring reports in order to capture and highlight any issues in the data transformation process into Information and knowledge and highlight their impact on the decision making process

4. Generate Information Quality Dashboards to provide senior management with proper visual monitoring and tracking tools to monitor the defects in business processes, SOPs or data transformation, and track the progress of eliminating the defects.

5. Validate and verify that the transformation rules, selection criteria, and filtration criteria used in reports and analytical models match the defined standard for each data element in order to ensure the accuracy and integrity of the decision making process.

6. Monitor and report any inconsistencies, uniqueness and incompleteness issues in the business terms, aggregation methods, and business rules definitions in the enterprise business glossary to maintain the consistency of information .

7. Collaborate with other business areas that are sourcing and consuming information and analytics to align expectations as part of developing requirements, creating and executing business plans in order to ensure following the Information quality guidelines.

8. Apply the information and analytics governance framework including the management of business rules, operating model, information and analytics related policies and standards in order to deliver a smooth operation process.

9. Participate in the required research and POCs to explore and implement new technology trends and complex information and analytics governance use cases in order to enhance the enterprise data governance operating model.

10. Apply the data management framework including the management of data, information and analytics operating model, data policies and standards in order to deliver a smooth operation process.

Policies, Processes and Procedures

11. Follow all relevant department policies, processes, standard operating procedures and instructions so that work is carried out in a controlled and consistent manner

Day-to-day Operations

12. Follow the day-to-day operations related to own jobs in the department to ensure continuity of work

Compliance

13. Comply with all relevant CBE regulations, banking laws, AML regulations and internal policies and code of conduct in order to maintain sound legal position and mitigate any potential risks

14. Monitor and ensure that Information and Analytics related decisions, processes, and controls subject to Data transformations are auditable;

• Business Glossary should be timely updated to reflect the real situation.
• Information architecture should be always up-to-date and reflecting the existing facts.
• Documentation should be available to support compliance-based and operational auditing requirements.