Model Assurance Framework Engineer
2 weeks ago
Model Assurance Framework Engineer
Job Description:
As a Model Assurance Framework Engineer, you will be tasked with designing, implementing, and maintaining a robust framework to ensure the quality and reliability of our models. You will collaborate closely with our development teams to integrate best practices and standards into the model development lifecycle.
Your responsibilities will include working alongside cross-functional teams to establish processes and methodologies for validating models, identifying risks, and implementing mitigation strategies. Additionally, you will contribute to the continual enhancement of our model assurance framework by remaining abreast of industry trends and emerging technologies.
Key Responsibilities:
Develop and implement a comprehensive model assurance framework to guarantee the accuracy, reliability, and compliance of our models.
Collaborate with stakeholders to define requirements, establish standards, and design processes for model validation and verification.
Design and automate test cases, scripts, and procedures to assess the performance and functionality of models under various scenarios.
Conduct thorough reviews of model documentation, code, and assumptions to identify potential errors or discrepancies.
Work closely with data scientists, analysts, and developers to integrate quality assurance practices into the model development lifecycle.
Perform root cause analysis of model failures and implement corrective actions to prevent recurrence.
Provide technical guidance and support to teams on best practices for model testing, validation, and deployment.
Stay informed about industry regulations, standards, and emerging technologies related to model assurance and incorporate relevant insights into our framework.
Participate in cross-functional meetings, workshops, and training sessions to foster collaboration and knowledge sharing across teams.
Qualifications:
Bachelor's degree or higher in computer science, engineering, mathematics, or a related field.
Proven experience in developing and implementing quality assurance frameworks for complex software systems or mathematical models.
Strong proficiency in programming languages such as Python, Java, or R, with experience in test automation and scripting.
Solid understanding of statistical methods, mathematical modelling techniques, and data analysis tools.
Familiarity with regulatory requirements and industry standards related to model risk management (e.g., SR 11-7, CECL, IFRS 9).
Excellent analytical skills with the ability to identify patterns, trends, and anomalies in data.
Effective communication and collaboration skills, with the ability to work across teams and influence stakeholders at all levels.
Detail-oriented mindset with a passion for quality and continuous improvement.
Preferred Qualifications:
Master's degree or PhD in a quantitative discipline (e.g., statistics, applied mathematics, econometrics).Experience with machine learning frameworks and techniques for model validation and testing.
Knowledge of software development methodologies such as Agile, Scrum, or DevOps.
Certification in quality assurance or related field (e.g., Certified Software Quality Engineer, Certified Analytics Professional).
Experience working in regulated industries such as finance, healthcare, or insurance.
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