Standard / Permanent
“Risk - Strategic Analysis & Reporting” (Risk - SAR) is a transversal team within the Risk Function covering all businesses, countries where the Group is established. Its main missions are centered on:
· Data management,
· Reporting of market, counterparty, liquidity, interest rate risks
· Strategic risk analysis, including coordination of Risk forums,
· Credit and market stress testing.
The position in the field of Data management, reports hierarchically to the Credit Data Steward, who reports to the Head of SAR Americas.
The Data Quality Analyst supports the Credit Data Steward in his mission
The Data Steward is responsible for the coordination of all data governance activities pertaining to Credit risk and works with Data Governance, other Data Stewards, Data Owners, Data Process Owners, and Data Custodians to create alignment and horizontal integration of data and information across all appropriate business areas. He or she is responsible for obtaining buy-in and participation from leadership teams in the business area for data governance activities and has significant influence in setting the data governance policies, standards, and goals for the organization.
The Data Quality Analyst supports the Credit Data Steward in his operational duties:
Review of Data Profiling
Data Profiling is the process of gaining an understanding of the existing data relative to the data quality methodology. Data is profiled and a report is produced on definitional and statistical attributes. Identified issues will be analyzed and remediation defined as needed.
A key data element is data that has a material impact on business operations and regulatory compliance. The initial focus of Data Governance is on identifying key data elements deemed a high priority for IHC. The Data Management team is responsible for coordinating all changes to Data Community KDEs through active leadership of the running change and change implementation processes.
Business Data Quality Rules
Data Quality Business Rules are the business checks or conditions that are applied on the source data. The Data Management team is responsible for defining the data quality objectives Identify data quality requirements and standards as well as reviewing of data quality reports.
IMR management is the maintenance of a comprehensive list of all known data issues across the platform. It includes oversight and tracking of actions to resolve issues and improve the quality of reported data. The Data Management team is responsible for:
- Identifying issues for IMR using output from data profiling, and detection of issues based on expert judgement through the maintaining of regular interactions with various risk teams.
- Resolving open issues under his ownership
- Signing-off and approving on issue closures
Data Lineage entails the systematic capturing and linking of information related to the creation and consumption of data elements through business processes and technology. The Data Management team is responsible for initiating, facilitating, and tracking completion of Data Lineage analysis and documentation.
Data Trace is a process by which data transformations are audited for accuracy and integrity. It ensures data to the Regulatory Reports are processed, transformed and reported accurately as per the Regulatory Guidelines. The Data Management team is responsible for:
- Liaising between Data Trace team and Data Owners to explain and clarify data observations identified during Data Trace review.
- Reviewing Data Lineage documentation with stakeholders and obtains endorsement/approval
- Coordinating the collection of required documents for Data Trace
Data Management entails working with the business and IT to maintain controls and reconciliations for reference by internal and external entities, as well as the coordination of quality of all referential data across IHC. The Data Management team is responsible for:
- Identifying and executing robust and continuous improvement opportunities within the enterprise data management processes in the applicable systems
- Periodic validation of controls and reconciliations
- Identifying new data sources in his or her data domain as required
Bachelor’s Degree in Finance or related field.
A minimum of 3 years’ experience in relevant field to Data Quality Management ex: IT architecture background
Knowledge of credit risk topics
Proficiency in Microsoft Office (Word, Excel, PowerPoint).
Ability to build and maintain relationships with different stakeholders.
FINRA Registrations Required:
- Not Applicable