Associate Risk Analyst
Job Details
- Location:
- Hartford, CT
- Category:
- Risk Management
- Employment Type:
- Full time, Hybrid
- Job Ref:
- R2626104-168
We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
Description:
Operational Risk Management (ORM) is seeking a highly motivated individual with a passion for the risk management to join the Model Risk Management Team. The Model Risk Management Team manages model risk across The Hartford by working with the businesses to validate critical models and implementing consistent modeling policies and standards.
In this role, the Associate Risk Analyst will support model governance work, assist with model validations, conduct research on emerging risk management best practices/ industry perspectives, and support emerging AI/ Gen AI risk projects.
Responsibilities:
- Support for day-to-day model validation and governance activities, including:
- Support management of model inventory and assisting in the maintenance of model policy and standards.
- Identifying opportunities to improve risk metrics and reporting capabilities.
- Assisting in the validation of models by reviewing assumptions, testing outputs, and documenting findings in collaboration with validators and model developers.
- Identify opportunities to enhance, automate, and streamline model validation practices
- Conduct research on emerging model risk management practices, AI/GenAI governance, and regulatory developments.
- Assist in developing monitoring and reporting capabilities for traditional, AI, and Generative AI models.
- Contribute to special projects focused on governance enhancements, operational excellence, and continuous improvement.
- Provide support for ad hoc requests related to new business initiatives and cross-functional collaborations
Qualifications:
- Bachelor’s degree in mathematics, statistics, data science, actuarial science, or a related discipline.
- 2+ years of professional experience; prior experience in the insurance industry is preferred.
- Strong analytical and critical thinking skills with the ability to test hypotheses and solve complex business problems.
- Proven ability to manage and prioritize multiple responsibilities and deadlines in a dynamic environment.
- Familiarity with programming languages such as Python, R, VBA, or similar.
- Effective communicator with the ability to convey technical concepts to both technical and non-technical audiences.
- Collaborative team player with a demonstrated ability to build strong working relationships and contribute independently.
- Results-driven, detail-oriented, and accountable, with a flexible and adaptable mindset.
- Committed to continuous improvement and proactive problem-solving.
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:
$69,200 - $103,800Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us
We believe every day is a day to do right.
And that belief has guided us for over 200 years. Showing up for people isn’t just what we do, it’s who we are. We’re devoted to finding innovative ways to serve our customers, communities and employees – continually asking ourselves what more we can do.
And while how we contribute looks different for each of us, it’s these values that drive all of us to do more and to do better every day.
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