Model Validation 2nd LOD Sr. Analyst

Citi • Irving, TX

1d • Hybrid

About The Position

Citibank, N.A. seeks a Model Validation 2nd LOD Sr. Analyst for its Irving, TX location. Duties: 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. A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite in accordance with Citi policies and protocols.

Requirements

• Bachelor’s degree, or foreign equivalent, in Engineering (any), Statistics, Mathematics, Economics, or a related field, and 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; and 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.

Responsibilities

• 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.

Benefits

• In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards.
• Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs.
• Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level