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Citibank, N.A. seeks a Model Validation 2nd LOD Sr. Analyst for its Irving, TX location. A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite in accordance with Citi policies and protocols.
Job Responsibility:
Develop, enhance, and validate the methods of measuring and analyzing risk, for all risk types including market, credit and operational
Develop, validate, and strategize uses of scoring models and scoring model related policies
Conduct statistical analysis for credit risk and fraud related projects and data modeling/validation
Apply quantitative and qualitative data analysis methods including SAS programming, Python language, and Structured Query Language (SQL) to extract, transform, and analyze data
Prepare statistical and non-statistical data exploration, validate data, and identify data quality issues
Conduct data analysis, data mining, read and create formal statistical documentation, and work with Technology to address issues
Analyze and interpret data reports and make recommendations addressing business needs
Use predictive modeling methods, optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences
Generate statistical models to improve methods of obtaining and evaluating quantitative and qualitative data and identify relationships and trends in data and factors affecting research results
Validate assumptions and escalate identified risks and sensitive areas in methodology and process
Automate data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes, and provide documentation and presentations
Requirements:
Bachelor’s degree, or foreign equivalent, in Engineering (any), Statistics, Mathematics, Economics, or a related field
Five (5) years of experience in the job offered or in a related quantitative occupation developing, enhancing, and validating the methods of measuring and analyzing risk
Five (5) years of experience must include: Validating traditional statistical (linear regression models, logistic regression, classification and regression decision tree models), machine learning, and artificial intelligence models for consumer valuation models
Assessing model risk across the model life-cycle by performing statistical, data, and quantitative analysis for model development using analytical and business tools including advance excel, VBA codes, SAS/4GL, SQL, R, and Python
Providing effective challenge to the model development process, including identifying model limitations, including data and soundness issues, performance weaknesses, usage restrictions
Performing validation tests and diagnostic analyses to evaluate the soundness an performance of the developed models
Creating formal and detailed statistical documentation with supporting analyses, testing results, and rationales for key decisions and ensuring documentation meets regulatory guidelines and industry standards
In the alternative, employer will accept a Master’s degree and three (3) years of experience
What we offer:
medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
discretionary and formulaic incentive and retention awards