Senior Model Risk & AI Validation Analyst

The Hartford; Hartford (CT); Hybrid; USD 108,000 - 162,000; Full time

Job summary

The Hartford's Model Risk Management team is seeking a Senior Analyst to lead validation of models across the enterprise. You will assess data inputs, methodologies, and outputs, and report findings to stakeholders while promoting best practices in model risk management.

Qualified candidates have an advanced degree in a quantitative field, 5+ years in insurance analytics, familiarity with programming languages such as Python, R, SAS/SQL, and strong communication skills to explain complex

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 programming languages/technology platforms including Excel/VBA, R, Python, SAS/SQL, C++, Java.
• Project management skills are an important plus.

Responsibilities

• Perform model validations of critical models across The Hartford to ensure effectiveness and proper use.
• Ensure model calculations are accurate and appropriate for intended use.
• Assess key data inputs and assumptions for accuracy and suitability.
• Review model outputs for correctness and downstream usage.
• Deliver clear, structured validation reports and governance accountability.

Skills

Project management

Analytical thinking

Communication

Independent worker

Education

Advanced degree in quantitative field

ACAS/ASA or FCAS/FSA designation or CFA preferred

Tools

Excel/VBA

R

Python

SAS/SQL

C++

Java

Job description

The Hartford's Model Risk Management team is seeking a Senior Analyst to lead validation of models across the enterprise. You will assess data inputs, methodologies, and outputs, and report findings to stakeholders while promoting best practices in model risk management.

Qualified candidates have an advanced degree in a quantitative field, 5+ years in insurance analytics, familiarity with programming languages such as Python, R, SAS/SQL, and strong communication skills to explain complex