Model Validation Specialist

Sumitomo Mitsui Banking CorporationCharlotte, NC
$95,000 - $140,000Hybrid

About The Position

The Associate, Model Risk & Validation (MRV) will support the independent validation and ongoing assessment of financial crime, risk, and other quantitative and non-quantitative models across the Firm. The role is responsible for executing validation testing, assessing model design and performance, reviewing model governance and documentation, and ensuring compliance with regulatory expectations and internal Model Risk Management (MRM) standards. The successful candidate will work closely with model developers, business stakeholders, and risk partners to identify model risks, evaluate model changes, and contribute to a strong model risk management framework. Exposure to Financial Crime Compliance domains, including AML, Fraud, Sanctions Screening, or Trade Compliance, is desirable; however, candidates with strong quantitative, analytical, and model risk management experience from other domains are encouraged to apply.

Requirements

  • Master’s degree in Statistics, Mathematics, Data Science, Computer Science, Engineering, or a related quantitative discipline, with 3–5 years of experience in Model Risk Management, Model Validation, AML/Fraud analytics, Financial Crime Compliance, or risk consulting within the financial services industry.
  • Strong understanding of model validation principles, statistical and data analytics techniques, and regulatory expectations related to AML, Fraud, Trade Compliance, AI/ML, and other risk models.
  • Proficiency in SQL and Python/R for data extraction, analysis, testing, and automation, with experience working with large datasets and exposure to cloud-based analytics environments (e.g., Azure).
  • Excellent analytical, problem-solving, and communication skills, with the ability to synthesize complex data, prepare clear and concise documentation, and effectively communicate technical concepts and validation results to both technical and non-technical stakeholders, including senior management, and auditors

Nice To Haves

  • Exposure to Financial Crime Compliance domains, including AML, Fraud, Sanctions Screening, or Trade Compliance
  • Familiarity with financial crime and risk management platforms such as Actimize, Fircosoft, world check, or similar systems is preferred

Responsibilities

  • Conduct independent validations of AML, Fraud, Trade Compliance, Artificial Intelligence/Machine Learning (AI/ML), and other quantitative and non-quantitative models, assessing conceptual soundness, data quality, methodology, implementation, controls, and ongoing performance.
  • Execute validation testing, including data analysis, independent replication, benchmarking, sensitivity analysis, back-testing, performance monitoring, and outcome assessment to evaluate model effectiveness and fitness for purpose.
  • Review model development documentation, governance frameworks, policies, procedures, and controls to ensure compliance with regulatory expectations and internal Model Risk Management (MRM) standards.
  • Assess model changes, including recalibration, tuning, segmentation, parameter updates, and design enhancements resulting from evolving business activities, market conditions, customer behavior, or risk appetite.
  • Identify model limitations, risks, and control weaknesses; communicate findings to model owners and senior stakeholders; and provide practical, risk-based recommendations for remediation.
  • Prepare clear, concise, and regulatory-ready validation reports, workpapers, and supporting documentation, and track remediation activities through closure.
  • Develop and enhance validation methodologies, testing frameworks, documentation templates, and automation solutions to improve consistency, efficiency, and coverage of validation activities.
  • Support internal audits, regulatory examinations, and governance reviews by providing validation evidence, analysis, and subject matter expertise.
  • Maintain current knowledge of AML, fraud, sanctions, trade compliance, AI/ML governance, and emerging regulatory and industry best practices.

Benefits

  • annual discretionary incentive award
  • competitive portfolio of benefits
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