Position Overview:
This role is a member of the Modeling & Analytics team, sitting alongside the CAT Modeling Analyst and CPAC Data Specialist. It is structured as a shared service, with a direct reporting line to the VP of Modeling & Analytics and a matrix reporting responsibility to support Marketing, the Personal Lines Business Unit, the Commercial Lines Business Unit (CPAC), and Claims. The position is built around three primary functions: performing catastrophe modeling work, building out a net-new predictive/statistical modeling capability for the team, and owning the ongoing build-out and maintenance of the group's Qlik/BI reporting technology on behalf of these business units. The ideal candidate is analytically strong, comfortable learning across disciplines, and motivated to grow the team's modeling and data-platform capabilities over time.
This opportunity is open to all J&J offices, Mount Pleasant preferred.
Base salary range: $80,000.00 - $110,000.00 ( no commission)
Job Responsibilities:
CAT Modeling
- Utilize catastrophe modeling software (e.g., RMS, AIR) to conduct in-depth analyses of natural and man-made catastrophe risks impacting the property portfolio.
- Contribute to the evaluation and quantification of catastrophe risk, supporting Personal Lines and Commercial Lines (CPAC) underwriting strategy and decision-making based on model outputs and insights.
- Validate and refine catastrophe models and data cleansing processes to ensure accuracy and reliability.
- Contribute to building out and enhancing J&J's view of risk.
- Analyze claims data in partnership with Claims to identify trends that improve underwriting and modeling accuracy.
- Stay informed on emerging trends and advancements in catastrophe modeling, integrating relevant insights into risk assessment processes.
Predictive Modeling & Statistical Analysis
- Develop and grow predictive modeling capability for the Modeling & Analytics team, a skill set that is net-new for the group.
- Maintain and enhance risk-based pricing predictive models for Personal Lines, the primary application of this capability, alongside predictive modeling that supports CAT modeling work.
- Apply statistical techniques to analyze portfolio performance, rate adequacy, and aggregate utilization, and build models that support underwriting and pricing decisions across Personal Lines and Commercial Lines (CPAC).
- Partner with the VP of Modeling & Analytics, Personal Lines, and CPAC to identify use cases where predictive/statistical modeling can improve decision-making and portfolio strategy.
- Stay current on predictive modeling methods and tools, and recommend approaches for building this capability out over time.
BI / Data Platform (Qlik)
- Own the ongoing build-out, maintenance, and enhancement of the team's Qlik/BI environment, including sourcing and structuring data from source systems for use in BI reporting.
- Build and maintain Qlik/BI applications, dashboards, and reports for Marketing, Personal Lines, Commercial Lines (CPAC), and Claims, evolving them as business needs change.
- Partner with Marketing, Personal Lines, CPAC, and Claims stakeholders on an ongoing basis to ensure BI tools remain valuable and relevant, and to translate new reporting needs into BI solutions.
- Maintain data integrity across the platform and continuously refine the data pipeline from source systems into Qlik to support scalability and long-term maintainability.
- Performs all other duties as assigned.
Education and Work Experience:
- 0-5 years of experience in insurance, data analysis, or a related analytical field; insurance experience preferred but not required.
- Bachelor's degree in Statistics, Mathematics, Risk Management, Data Science, Actuarial Science, or a related field.
- Proficiency in statistical analysis and data manipulation, with advanced Excel skills.
- Experience with SQL, VBA, R, or other data/programming languages preferred.
- Experience with BI technology such as Qlik, Tableau, or Power BI strongly preferred.
- Exposure to catastrophe modeling software (e.g., RMS, AIR) a plus.
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
- Legal authorization to work in the United States.
Knowledge, Skills & Abilities:
- Strong analytical skills and attention to detail, with the ability to interpret complex data sets.
- Ability to learn quickly across multiple disciplines, including CAT modeling, predictive/statistical modeling, and BI platform development.
- Comfort working on ambiguous, developing initiatives, particularly the buildout of a new predictive modeling capability.
- Exceptional time management skills and the ability to prioritize tasks effectively across multiple functions.
- Strong interpersonal skills and the ability to communicate complex findings to internal and external stakeholders.
- Adaptability to changing priorities and willingness to take on new challenges.
Typical Physical Demands:
- Requires the ability to sit or stand for long periods of time, occasional stooping, and reaching; may require lifting up to 25 pounds; requires normal range of vision and hearing with or without accommodations.
Employee Signature: ___________________ Date: ___________________
Education and Work Experience:
- 0-5 years of experience in insurance, data analysis, or a related analytical field; insurance experience preferred but not required.
- Bachelor's degree in Statistics, Mathematics, Risk Management, Data Science, Actuarial Science, or a related field.
- Proficiency in statistical analysis and data manipulation, with advanced Excel skills.
- Experience with SQL, VBA, R, or other data/programming languages preferred.
- Experience with BI technology such as Qlik, Tableau, or Power BI strongly preferred.
- Exposure to catastrophe modeling software (e.g., RMS, AIR) a plus.
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
- Legal authorization to work in the United States.
Knowledge, Skills & Abilities:
- Strong analytical skills and attention to detail, with the ability to interpret complex data sets.
- Ability to learn quickly across multiple disciplines, including CAT modeling, predictive/statistical modeling, and BI platform development.
- Comfort working on ambiguous, developing initiatives, particularly the buildout of a new predictive modeling capability.
- Exceptional time management skills and the ability to prioritize tasks effectively across multiple functions.
- Strong interpersonal skills and the ability to communicate complex findings to internal and external stakeholders.
- Adaptability to changing priorities and willingness to take on new challenges.