Manager- R&C

Role overview

Manager- R&C at IBM

The role supports the Bank's Model Risk Management (MRM) framework by conducting rigorous validations in accordance with regulatory requirements, including the U.S.

Responsibilities

• Perform independent validations and reviews of models/EUCs across the model lifecycle under supervision of the US team.
• Develop recommendations for model improvements and risk mitigation.
• Assist in maintaining the model inventory, model risk ratings, and issue tracking and remediation.
• Collaborate with bank MRM team, model developers, business units, risk management teams, and technology teams.

Preferred qualifications and skills

• Experience validating or developing risk, financial, or machine learning models is preferred.

Employment details

• Location: Bangalore [India]

About the employer

• India Enterprise Operations Professional Bangalore, IN Bangalore (0063) IBM India Private Limited Anti-money Laundering Artificial Intelligence Banking Basel II Credit Risk Critical Thinking Data Science Documentation Economics Education Finance Financial Services Forecasting Machine Learning Market Risk Mathematics Probability Theory Python Quantitative Analytics R Programming Language Regulations Remediation Risk Management Structured Query Language Stakeholder Engagement Statistics Validation Programming Languages Detail-oriented Stress Testing Current Expected Credit Losses Commitment Regression Analysis Model Risk Technical Proficiency Risk Fraud Lending Statistical Analysis System Programming Language Model Governance Verbal Communication Model Validation Model Risk Management Statistical Inference Quantitative Modeling Relationship Management Performance Monitoring

Additional role details

• The Model Validation Analyst is responsible for independently assessing the conceptual soundness, performance, implementation, and ongoing monitoring of models used across the Bank.
• Federal Reserve's SR 26-2 Guidance on Model Risk Management and applicable OCC and FDIC expectations.
• The analyst will evaluate a variety of quantitative and qualitative models, including credit risk, market risk, liquidity risk, stress testing, AML/fraud, capital planning, CECL, pricing, and machine learning models.
• The successful candidate will work under the supervision of the U.S. team, work closely with bank MRM team, model developers, model owners, business stakeholders, Internal Audit, and regulators to ensure models are fit for purpose and risks are appropriately identified and mitigated.
• Assess model conceptual design, methodology, assumptions, limitations, data quality, implementation, and usage.
• Conduct quantitative testing, including: Outcome analysis Benchmarking Back-testing Sensitivity analysis Stress testing Performance monitoring reviews Evaluate model development documentation and supporting evidence.
• Verify compliance with internal model risk policies and regulatory guidance.
• Assign validation findings and risk ratings based on established governance standards.
• Education Bachelor's degree in Statistics, Mathematics, Economics, Finance, Data Science, or related quantitative discipline Experience 2-5 years of experience in model validation, model development, quantitative analytics, data science, risk management, or related fields within banking or financial services, preferably for U.S. clients.
• Familiarity with model risk management frameworks and regulatory expectations.
• Technical Skills Strong understanding of statistical and quantitative modeling techniques.
• Knowledge of: Regression analysis Time series forecasting Classification models Machine learning methodologies Probability and statistical inference Proficiency in one or more programming languages: Python R SAS SQL Experience working with large datasets and analytical tools.
• Master's degree in a quantitative field.
• Experience validating: Credit risk models CECL models Stress testing models Market risk models AML/Fraud models Machine learning and AI models
• Experience or familiarity with: o SR 26-2 Model Risk Management Guidance o OCC Model Risk Management expectations o CECL framework o Basel regulations o Fair Lending and model governance requirements o AI/ML model risk considerations Competencies Strong analytical and critical thinking skills.
• Ability to independently challenge complex quantitative methodologies.
• Excellent written and verbal communication skills.
• Strong report-writing and documentation capabilities.
• Attention to detail and commitment to quality.
• Ability to manage multiple projects and deadlines.
• Strong stakeholder engagement and relationship management skills.
• Key Deliverables Comprehensive model validation reports.
• Validation test workpapers and supporting documentation.
• Findings and remediation tracking.
• Model performance monitoring assessments.