Associate Analyst- Model Risk Management

The role supports the Model Risk Management and AI Risk team in day-to-day activities covering model governance, AI risk governance, independent review support, model inventory administration, monitoring, issue tracking and management information. 

The position is designed for a fresh graduate or early-career hire who will develop a sound foundation in model lifecycle risk and the responsible use of artificial intelligence in banking.

Under supervision and with structured training, the role holder will assist with evidence gathering, analytical review, documentation and coordination across stakeholders. 

The role requires curiosity, attention to detail, sound quantitative aptitude, integrity and the ability to communicate clearly with technical and non-technical colleagues.

Provide proactive administrative, analytical and coordination support to the Model Risk Management and AI Risk team.

Assist in maintaining complete and accurate model and AI use-case inventory, including ownership, purpose, status, risk tier, validation, monitoring and approval information.

Support model identification, risk classification, initial screening and lifecycle governance activities using approved templates and procedures.

Assist with independent model and AI review activities by collecting documentation, checking data completeness, reproducing basic analyses and documenting observations under supervision.

Support basic quantitative testing using Excel and, as capability develops, Python, R or SAS for data quality, performance, stability, sensitivity, fairness and monitoring analyses.

Help review AI use cases for responsible AI considerations, including data quality, fairness, transparency, explainability, human oversight, privacy, security, robustness and appropriate use.

Support preparation of committee packs, dashboards, risk appetite reporting, regulatory assessments and management information for model and AI risk oversight.

Track validation plans, monitoring submissions, model or AI changes, conditions, findings and remediation actions, and follow up with stakeholders on agreed timelines.

Maintain clear working papers, evidence, version control and audit trails in line with approved policies, procedures and information-handling requirements.

Contribute to automation and process improvement opportunities that improve the quality, consistency and efficiency of governance, validation and reporting activities.

Participate in training and progressively build knowledge of banking models, AI and machine learning, model risk, responsible AI, statistics, regulation and ADIB governance processes.

Escalate incomplete information, control concerns, missed timelines or potential policy breaches 

Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, Artificial Intelligence, Quantitative Finance, Economics, Engineering, Actuarial Science or a related quantitative discipline.

Fresh graduate or up to two years of relevant internship or work experience. Banking experience is advantageous but not mandatory.

Foundation knowledge of statistics, data analysis, machine learning or model development concepts, with a strong willingness to learn risk governance and validation.

Good working knowledge of Microsoft Office, particularly Excel and PowerPoint. Exposure to Python, R, SAS, SQL, Power BI or similar analytical tools is advantageous.

Strong analytical, research, problem-solving and documentation skills, with careful attention to data quality and detail.

Clear written and verbal communication, professional judgement, teamwork, adaptability and commitment to continuous development.

Awareness of responsible AI, model risk, data privacy, information security or banking regulation is advantageous but not mandatory.