Head Model Risk Validation

Saaki Argus And Averil Consulting; Chennai District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Saaki Argus And Averil Consulting in Chennai, India, seeks an experienced Model Risk Validation Lead to build a robust validation function within a Global Capability Center. You will define governance, lead a team, and deliver independent validation across risk domains.

The role focuses on regulatory compliance, ongoing improvement, vendor management, and partnership with global Model Risk teams to raise validation standards.

Qualifications

• 14+ years of experience in Model Risk Management, Model Validation, or Model Development within banking or financial services.
• Strong understanding of mathematical finance, statistics, and quantitative risk modeling.
• Deep knowledge of model governance frameworks and regulatory expectations.
• Experience establishing or scaling offshore/GCC capabilities is highly desirable.
• Proven leadership experience building and managing high-performing teams.

Responsibilities

• Establish and operationalize the Model Risk Validation function within the GCC and define the target operating model and governance.
• Lead independent validation of financial and risk models across credit risk, IFRS 9/ECL, stress testing, and related areas.
• Review and challenge model assumptions, methodologies, limitations, and validation outcomes.
• Develop QA, peer review, and control testing processes; monitor KRIs and remediation progress.
• Manage external partners, define SLAs, and drive knowledge transfer to internal teams.
• Partner with global Model Risk Management and Risk teams; communicate validation outcomes to senior stakeholders.

Skills

Leadership

Stakeholder management

Analytical thinking

Problem solving

Model risk management

Python

R

SAS

SQL

Education

Bachelor's or Master's degree in Finance/Math/Stats/Economics/Engineering/Data Science

Tools

Python

R

SAS

SQL

Job description

Model Risk Validation Head GCCLocation: Chennai, IndiaAbout the Role:We are seeking an experienced Model Risk Validation Lead to establish and lead a Model Risk Management capability within a Global Capability Center. This is a strategic leadership role responsible for building a globally aligned model validation function, ensuring robust governance, and supporting enterprise-wide model risk management activities.The successful candidate will lead the development of a high-performing validation team, oversee model validation activities across multiple risk domains, and collaborate with global stakeholders to deliver high-quality, independent model validation services. This role offers the opportunity to shape a Center of Excellence for model risk management while driving operational excellence, regulatory compliance, and continuous improvement.Key Responsibilities:Strategy & Capability DevelopmentEstablish and operationalize the Model Risk Validation function within the GCC.Define the target operating model, governance framework, service scope, and long-term capability roadmap.Build, mentor, and lead a high-performing team of model validation professionals.Drive the transition from vendor-supported operations to a sustainable in-house delivery model.Model Validation & OversightLead independent validation of financial and risk models, including documentation reviews, methodology assessments, benchmarking, sensitivity analysis, independent testing, and validation reporting.Support validation activities across credit risk, IFRS 9/ECL, stress testing, compliance, and other financial risk models.Review and challenge model assumptions, methodologies, limitations, and validation outcomes.Ensure validation deliverables meet established governance, documentation, and quality standards.Governance & Risk ManagementDevelop and maintain quality assurance, peer review, and control testing processes.Support model inventory management, periodic reviews, change validations, ongoing monitoring, and model risk reporting.Monitor validation progress, remediation activities, key risk indicators (KRIs), and operational metrics.Escalate material model risks, control weaknesses, and delivery concerns to leadership as appropriate.Vendor & Delivery ManagementManage external partners supporting model validation activities.Define and monitor service levels related to quality, productivity, documentation, and turnaround time.Facilitate knowledge transfer and capability development within the internal team.Reduce vendor dependency through structured capability building and process maturity.Stakeholder ManagementPartner with global Model Risk Management, Model Validation, and Risk teams across multiple regions.Build trusted relationships with senior stakeholders and ensure effective communication on validation outcomes, risks, and remediation efforts.Operational ExcellenceOversee model validation operations, control testing, model risk reporting, and governance activities.Drive automation, process standardization, and continuous improvement initiatives to improve efficiency and scalability.Promote best practices across the model lifecycle and support the adoption of model lifecycle management tools.Required QualificationsBachelor's or Master's degree in Finance, Mathematics, Statistics, Economics, Engineering, Data Science, or a related quantitative discipline.14+ years of experience in Model Risk Management, Model Validation, or Model Development within the banking or financial services industry.Strong understanding of mathematical finance, statistics, and quantitative risk modeling.Experience validating credit risk, IFRS 9/ECL, stress testing, or other financial risk models.Deep knowledge of model governance frameworks and regulatory expectations.Experience establishing or scaling offshore/GCC capabilities is highly desirable.Proven leadership experience building and managing high-performing teams.Experience managing third-party vendors and hybrid delivery models.Familiarity with model lifecycle management tools and validation frameworks.Strong stakeholder management, communication, and influencing skills.Preferred SkillsStrong analytical and problem-solving abilities.Experience with statistical programming tools such as Python, R, SAS, or SQL.Knowledge of model lifecycle management, model governance, and regulatory standards.Experience driving automation and process improvement initiatives.Ability to work effectively with cross-functional and geographically distributed teams.