The AML Validation Team is part of Citi’s Global Model Risk Management (MRM) Group. The main objective of validation is to ensure that models are used appropriately by the business and that model users are aware of the models’ limitations and weaknesses that should be mitigated by compensating controls. MRM operates independently of the model development departments to ensure the objectivity of the validation process.

The Data Statistician / Model Validator will execute complex statistical analysis, data visualizations, data processing and will follow the globally consistent methodology, but is expected to have a high level of initiative and creativity and suggest enhancements to the current methodology. He/she will work in global team of experienced statisticians.

Responsibilities:
• Support validation of predictive models (models for binary outcome, decision trees, linear regression, machine learning) using SAS/R statistical software
• Perform critical review of model development... process and obtained results. Perform effective challenge for models and build challenger models
• Apply statistical methods to organize, analyze, and interpret data to perform model validations.
• Provide data pulls and reports directly from Oracle Database.
• Conduct annual model performance assessments to ensure existing models are working as intended and meet the criteria and /or make model improvement recommendations.
• Prepare model validation reports in a detailed, structured and clear manner, highlighting risks and limitations of the model
• Use visualization techniques to display data and the results of analysis in clear straightforward presentations that can be understood by non-technical readers.
• Distribute validation reports and consult with model and business owners and other stakeholders such as senior management, on model validation results.

Qualifications:
• Higher education (Bachelor or higher) in statistics/mathematics/technical science. Degree in economics/banking may be considered if strong analytical skills proved.
• Knowledge of predictive modeling techniques (models for binary outcome, decision trees, linear regression, machine learning)
• Experience in data mining methods and their application in business will be considered as asset
• Strong programming and statistical/data analytical skills in SAS 4GL and SQL.
• Statistical/data analytical skills including both calculation and interpretation of outcome
• Experience with relational databases such as Oracle, SQL Server, and Data Marts/Data Warehouses.
• Experience in reporting the results of analysis in clear written form, and in presenting the findings.
• Very good English language skills.
• Experience in designing AML detection and monitoring systems will be considered as asset.
• Knowledge of Mantas will be considered as asset.

Education:
• Bachelor’s/University degree or equivalent experience

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Job Family Group:
Risk Management

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Job Family:
Risk Analytics, Modeling, and Validation

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Time Type:
Full time

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