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Open nowPosted yesterday

Senior Officer - Risk Data Management

ADIB150 open roles

Where
United Arab Emirates
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Your applicationOpen nowSenior Officer - Risk Data ManagementADIB · United Arab Emirates

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. ADIB postings stay open a median of 17 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted yesterday

ADIB median: 17 days open

The posting

Job Description

Role: Senior Officer - Risk Data Management

Location: Abu Dhabi

Role purpose:

  • Prepare, derive and validate variables and datasets required for the development, recalibration, validation and implementation of Application Scorecards and Behavioural Scorecards.
  • Provide the Risk Modelling team with accurate, model-ready datasets for A-Score and B-Score development.
  • Support accurate implementation of approved scorecards in production as part of the model implementation exercise.
  • Automate BAU activities, including ingesting multi-source data in an agreed format and loading it into the Azure/CML database.
  • Develop SAS-based automation on the existing SAS Risk Stratum engine and deploy ad-hoc changes as requirements arise.
  • Coordinate with Model Development, Model Validation, Business and IT teams to resolve data and implementation issues, escalating where required.
  • Run the existing SAS suite that loads LGD model data, including loss, recovery and post-default event data from source systems.
  • Prepare data for CBUAE regulatory reporting and BRF requirements.

Key accountabilities of the role:

Scorecard Variable & Data Preparation:

  • Prepare, derive and validate variables and analytical datasets required for Application and Behavioural Scorecard development, recalibration, validation and implementation.
  • Interpret approved business definitions, model specifications and variable logic and convert them into controlled SAS and SQL programs.
  • Consolidate source data, perform data-quality checks and deliver complete datasets in the agreed structure and format.
  • Investigate data gaps, anomalies and reconciliation differences and coordinate their resolution with relevant stakeholders.
  • Prepare data for CBUAE regulatory reporting and BRF requirements.

Model Implementation & Testing:

  • Support model implementation by providing accurate insights into the underlying data and model logic.
  • Perform unit testing, system integration testing, user acceptance support, reconciliation and parallel-run validation.
  • Deploy SAS models to the IFRS 9 risk engine using SAS DI jobs, and benchmark results across the Development and UAT environments.

SAS Engineering & Data Management:

  • Develop, maintain and optimise SAS and SQL programs used for variable preparation, scorecard implementation and recurring data processing.
  • Support model deployment using SAS Data Integration, SAS Studio and related SAS platforms.
  • Develop controlled data pipelines and maintain data lineage between source systems, SAS processes, modelling databases and downstream solutions.
  • Execute relevant business-as-usual activities and provide technical support for implemented models.

Automation & Continuous Improvement:

  • Automate recurring data preparation, validation, reconciliation and model implementation activities.
  • Review and optimise existing SAS implementation code to improve efficiency, maintainability and control.
  • Identify and implement SAS-based automation opportunities to reduce manual intervention and support the Provisioning, CBUAE Sup-Tech Risk Model BRFs.
  • Support other risk model implementation and regulatory data automation activities where required.

Specialist skills / technical knowledge required for this role:

  • Strong hands-on expertise in SAS programming, SAS Data Integration, SAS Studio and SQL.
  • Practical experience preparing and deriving variables for Application and Behavioural Scorecards.
  • Experience implementing scorecards or risk models, including testing, reconciliation and production deployment.
  • Good understanding of data quality, data lineage, reconciliation, model implementation controls and documentation.
  • Ability to review and optimise SAS code and develop efficient, controlled data pipelines.
  • Working knowledge of relational database management systems and Oracle.
  • Exposure to Python or SAS for analytics and automation.
  • Strong analytical, problem-solving, documentation, communication and stakeholder-management skills.

Previous experience required (if any):

  • Minimum 3–5 years of relevant experience in SAS development, risk data management, scorecard/model implementation, analytics or automation within banking or financial services.
  • Demonstrated hands-on experience preparing variables and datasets for Application or Behavioural Scorecards.
  • Experience translating approved model specifications into SAS- or SQL-based implementation logic.
  • Experience working with Model Development, Model Validation, Business and IT stakeholders on controlled production implementation.
  • Experience maintaining data-quality reports, lineage, implementation documentation and test evidence.
  • Experience automating recurring modelling, data-management or risk-reporting processes.
  • Experience with SAS Viya, Python, SAS MRM would be an advantage.
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