Data Scientist role emphasizing business insights and collaboration in insurance analytics. Involves working with clients and analyzing data for problem solving in various functional areas.
About the role
- Risk Manager leading efforts in model validation for critical models at The Hartford. Collaborating with teams to ensure models perform effectively for various business purposes.
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
- Build strong working relationships with key partners across the enterprise, including Data Science, Property & Casualty, Group Benefits, HIMCO, and a number of Corporate functions
- Pro-actively stay informed of department initiatives, deliverables, and reporting
- Assist in improving The Hartford’s Model Risk Management function, by monitoring external environment, implementing best practices, recommending process improvements, and evolving standards/guidelines
Requirements
- 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 Python, R, SAS/SQL, Excel/VBA
- Practical experience with predictive modeling/data science techniques
- Demonstrated experience and consistency in meeting deadlines while adapting to shifting priorities
- Strong analytical, critical and investigative thinking skills
- Solid verbal communication, listening, influencing, and written communication skills
- Ability to act independently with little direction, proactive self-directed accountability
- Solution oriented creativity and innovative thinking.
Benefits
- short-term or annual bonuses
- long-term incentives
- on-the-spot recognition
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