5-7 years of hands-on experience in statistical and AI/ML model development or validation
Strong understanding of quantitative modeling methods, particularly for Finance predictive models
Proficient in programming languages like Python, R, SQL, or SAS
Excellent communication skills for presenting complex findings to diverse audiences
Experience with regulatory requirements related to model validation and risk management
Responsibilities
Perform hands-on validation and review of quantitative models
Challenge model assumptions and limitations to ensure robustness
Present validation findings to model developers, offering actionable remediation
Document validation processes and outcomes in detailed reports
Support internal audits and regulatory exams with validation methodologies
Act as a subject matter expert on modeling and risk management practices
Conduct research and develop advanced tools to enhance the validation process
Benefits
Opportunities for continuous learning and professional development
Exposure to cutting-edge AI and ML technologies
Collaborative work environment with cross-functional teams
Engagement with regulatory entities and industry practices
Access to proprietary tools and data for validation projects
Full Job Description
Job Description
Must Have Technical/Functional Skills
Hands-on experience in statistical and AI/ML model development or validation, with a strong understanding of quantitative modeling methods (including AI/ML algorithms) used for various Finance predictive models
Proficiency in programming languages such as Python, R, SQL or SAS.
Excellent written and verbal communication skills to clearly articulate complex technical findings to both technical and non-technical stakeholder.
Roles & Responsibilities:
Perform hands-on quantitative model validation/review. This includes testing the model's conceptual soundness, data accuracy, methodology, and ongoing performance through techniques like backtesting, benchmarking, and stress testing, etc.
Provide an effective challenge throughout the model validation/review to ensure that models are robust, and all assumptions and limitations are justified.
Present findings, weakness and/or observations identified from the validation/review to model developers/owners and provide them with executable finding remediations.
Prepare detailed validation reports and memos that document the validation approach, findings, and conclusions.
Participate in internal audits and regulatory exams by presenting validation results and methodologies and assisting in the remediation of any audit or exam findings.
Act as a subject matter expert on modeling techniques, risk management practices, and regulatory trends. This involves performing research and developing advanced analytical tools or benchmarking models to aid the validation process.
