Model Validation Analyst. Sr. (Remote, Hybrid or Onsite)

Job Summary
The Senior Model Validation Analyst is a key contributor to the Model Risk Management (MRM) function, responsible for independently validating a wide range of models used across the enterprise (e.g., Treasury, Credit Risk, Marketing, Financial Crimes Unit, etc.). This role ensures models are conceptually sound, statistically robust, and compliant with regulatory expectations. The ideal candidate will bring deep quantitative expertise, strong communication skills, and a proactive mindset to enhance model governance and risk oversight.
Key Responsibilities

• Lead and execute comprehensive validations of models used in credit risk, market risk, operational risk, stress testing, capital planning, financial forecasting, marketing, financial crimes (fraud), BSA/AML, etc. This includes internally and externally developed models.
• Stay abreast of evolving regulatory guidance (e.g., SR 11-7, OCC 2011-12, Basel III, CECL) and industry best practices (e.g., NIST guidance on AI).
• Assist in the evaluation of AI/ML models and contribute to the development of responsible AI validation practices.
• Evaluate model design, data quality, assumptions, limitations, and performance metrics using advanced quantitative techniques.
• Develop challenger models or benchmarking approaches to assess model performance and reasonableness.
• Prepare detailed validation reports that clearly articulate findings, limitations, and recommendations for remediation or enhancement.
• Present validation results to model owners, senior management, and governance committees.
• Monitor ongoing model performance and support periodic revalidations and model change assessments.
• Contribute to the development and refinement of model risk policies, procedures, and validation frameworks.
• Collaborate with internal audit, compliance, and regulatory teams during examinations and audits.
• Support the development and implementation of model risk analytics and reporting tools.
• Mentor and provide technical guidance to junior team members and analysts.
• Participate in cross-functional working groups and model governance forums.
• Identify opportunities to automate validation processes and improve efficiency through scripting and tool development.

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.
Education:
Master's or Ph.D. in a quantitative field such as Statistics, Mathematics, Financial Engineering, Economics, Operations Research, or related discipline.
Experience:

• Master's degree and five (5)+ years of experience in model validation, model development, or quantitative risk management in a financial services company, insurance company, or consulting firm.
• OR a PhD and three (3)+ years of experience in model validation, model development, or quantitative risk management in a financial services company, insurance company, or consulting firm.
• Must have a strong understanding of statistical modeling, machine learning, and financial modeling techniques.

Required Knowledge, Skills and Abilities:
Technical Skills:

• Proficiency in programming languages such as Python, R, SAS, or MATLAB.
• Experience with data visualization and reporting tools (e.g., Power BI, Tableau).
• Familiarity with model governance platforms and documentation standards.

Soft Skills:

• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to manage multiple priorities and work independently in a fast-paced environment.