Model Validation Analyst. Sr.

Job Summary

Performs independent validation activities on highly complex models enterprise-wide, including Machine Learning and other Artificial Intelligence approaches, that support Synovus key strategic objectives. Complies with regulatory guidance and the Synovus Model Risk Management policy while providing effective challenge and verification that models are performing as expected in line with their design objectives and business uses.

Job Duties and Responsibilities

• Works closely with model owners, developers, and users to independently perform comprehensive validations of high impact models in compliance with regulatory guidance and Synovus policies and procedures. The scope of validation may include a review and effective challenge of the underlying assumptions, theory, empirical evidence, implementation, limitations, and results and context of reports of the model being validated.
• With minimal guidance from the Director or more senior analysts, validates models and analytical tools in the areas of fraud monitoring, cybersecurity, credit scoring, marketing, BSA/AML/OFAC and Consumer Compliance, market risk, operational risk, strategic risk, finance and accounting, loan pricing, deposit pricing, loan valuation, and capital adequacy to include stress testing (not all inclusive).
• Documents and presents observations to model owners, developers, and users; recommends management action plans and tracks remediation progress. Presents results to Executive or Senior Management, as appropriate.
• Conducts ongoing monitoring such as confirming that models are appropriately implemented, used, and performing as intended; performs outcome analysis (such as back-testing and benchmarking).
• Provides oversight and execution to the model risk management policies and procedures for the organization.
• Consults with model owners, developers, and users on model development including the design of effective model operational controls.
• Understands how model validation efforts support quantitative and qualitative reporting activities for data driven business decisions, as well as regulatory and risk compliance.
• Reviews the maintenance of existing models and enhancements implemented over time to mitigate negative feedback from regulators.
• Remains current on modeling trends, techniques, tools and best practices. Identifies emerging trends in technology as opportunities for future growth and development. Mentors less experienced team members in validation, the development and design of predictive models, and analyzing data as requested.
• Participates in activities and maintaining documentation related to developing innovations that enhance model validation and governance processes.
• Serves as subject-matter-expert resource by providing training/guidance to less experienced team members.
• Each team member is expected to be aware of risk within their functional area. This includes observing all policies, procedures, laws, regulations and risk limits specific to their role. Additionally, they should raise and report known or suspected violations to the appropriate Company authority in a timely fashion.
• Performs other related duties as required.

The information on this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.

Synovus is an Equal Opportunity Employer committed to fostering an inclusive work environment.

Minimum Education:

Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, or Economics or an equivalent combination of education and experience.

Minimum Experience:

• 7-10 years of related work experience, or relevant Master's degree with five years of related work experience (three if in financial services), or Ph.D. in relevant quantitative discipline with three years of related work experience in financial services
• Required Knowledge, Skills, & Abilities:
• Specialized training and work experience with a very strong background of statistical analysis and data modeling to include multivariate analysis, logistic regression, non-linear modeling, machine learning and other artificial intelligence approaches, and similar techniques
• Knowledgeable of model risk management and associated regulatory requirements and guidance
• Strong proficiency in programming tools SAS/R/Phython, and Microsoft Excel
• High degree of knowledge of database management and file access methods
• Extensive experience in the application of structured analysis and technical design techniques and experience using a wide range of interpretive analysis tools
• Ability to present and explain technical information in a way that establishes rapport, persuades others and promotes understanding.
• Strong project management skills