Sr Analyst Model Risk & AI, Data Science and Actuarial Model Validation

The Model Risk Management team manages model risk across The Hartford by validating these models, implementing consistent policies and standards, and maintaining appropriate model oversight. As part of the team, this role will focus on validating models throughout The Hartford and reporting results to key internal stakeholders. Through the validation process, supplementary responsibilities include educating on modeling best practices and spreading model risk awareness across the enterprise. Additionally, this role will also support the maintenance of the enterprise model risk management framework, including policies, standards, procedures, and governance processes.

Responsibilities:

• Perform model validations of critical models used across The Hartford’s functional areas and lines of business to ensure models are performing effectively and efficiently

• Ensure model calculations are accurate and appropriate for intended use
• Assess key data inputs and assumptions for accuracy and appropriateness
• Review model outputs for accuracy and appropriate downstream usage
• Deliver effective challenge to key modeling elements such as inputs, calculations, outputs, conceptual soundness, monitoring & controls, documentation, etc.
• Identify findings and recommendations to mitigate model risk, compile clear, concise and well-structured model validation reports, perform in-depth assessments of model risk, perform governance accountabilities related to findings tracking, remediation testing, and validation

• Perform governance accountabilities related to findings tracking, remediation testing, and validation
• Strengthen partnerships with Data Science and Actuarial teams to keep model risk practices aligned with the proliferation and sophistication of modeling, promote proactive risk management, and share best practices.
• Assist in improving The Hartford’s Model Risk Management function, by monitoring external environment, implementing best practices, recommending process improvements, and evolving standards/guidelines

Qualifications:

• Advanced degree in Statistics, Applied Mathematics, Actuarial Science, Computational Science, Quantitative Economics, Engineering, or similar applied analytical field
• 5+ years of P&C, Group, Life or related insurance product experience
• ACAS/ASA or FCAS/FSA designation and/or CFA preferred
• Familiarity with different programming languages/technology platforms including Excel/VBA,
• R, Python, SAS/SQL, C++, Java
• Practical experience with predictive modeling / data science techniques preferred
• Project management skills an important plus
• Familiarity with Supervisory Guidance on Model Risk Management (SR 11-7/ SR 26-2, PRA SS1/23) viewed as favorable
• Ability to act independently with proactive self-directed accountability and demonstrated experience and consistency in meeting deadlines while adapting to shifting priorities
• Strong analytical, critical and investigative thinking skills
• Demonstrated commitment to lifelong learning with a strong desire for continuous development to keep pace with evolving modeling techniques and AI technologies.
• Solution oriented creativity, innovative thinking, and challenging the status quo.
• Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders across the enterprise.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$108,000 - $162,000

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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