Model Risk Validation Analyst (W2, Local only) - PTR Global

Job Title: Model Validation Analyst

Location: Irving, TX (3 days onsite - Hybrid)

Duration: 06 months initial contract with extension for longer term

Job Description:

The Model Validation Analyst accomplishes results through the management of professional team(s) and department(s). Integrates subject matter and industry expertise within a defined area. Contributes to standards around which others will operate. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the entire function. Requires basic commercial awareness. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Has responsibility for volume, quality, timeliness and delivery of end results of an area. May have responsibility for planning, budgeting and policy formulation within area of expertise. Involved in short-term planning resource planning.Full management responsibility of a team, which may include management of people, budget and planning, to include duties such as performance evaluation, compensation, hiring, disciplinary and terminations and may include budget approval.

Responsibilities:

• Manages model risk across the model life-cycle including model validation, ongoing performance monitoring and annual model reviews.
• Produces analytics and reporting used to manage risk for economic scenario expansion models.
• Assists in the development of analytic engines for business product lines.
• Conducts statistical analysis for risk related projects and data modeling/validation.
• Applies quantitative and qualitative data analysis methods including SAS programming, Structured Query Language (SQL) to extract, transform and analyze data.
• Prepares statistical and non-statistical data exploration, validate data, identify data quality issues.
• Conducts data analysis, data mining, read and create formal statistical documentation, reports and work with Technology to address issues.
• Analyzes and interprets data reports, make recommendations addressing business needs and communicates results to diverse audiences.
• Conducts analysis and packages it into detailed technical documentation report for validation purposes sufficient to meet regulatory guidelines and exceed industry standards.
• Participates on teams to solve business problems.
• Manages stakeholder interaction with model developers and model validation teams during the model life-cycle.
• Possess general knowledge of model assumptions, mathematical formulation, model testing, performance metrics and model implementation.
• Contributes to strategic, cross-functional initiatives within the organization.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency, as well as effectively supervise the activity of others and create accountability with those who fail to maintain these standards.

Qualifications:

• 6-10 years experience
• Consistently demonstrates clear and concise written and verbal communication skills
• Self-motivated and detail oriented
• Demonstrated project management and organizational skills and capability to handle multiple projects at one time .
• Be comfortable interfacing with business clients. proficiency in handling very large data sets.
• Experience in a quantitative role in risk management at a financial institution with experience in either model development or validation.
• Good knowledge and understanding of a variety of model development and validation testing techniques covering risk models.

Plusses:

• Practical experience using Python or similar statistical software to run model performance test.

Education:

• Bachelors/University degree or equivalent experience in a quantitative discipline, potentially Masters degree