Quant Associate Financial models

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.