Analyst, Modeling and Analytics

Johnson & Johnson, Inc.; Mount Pleasant (SC); On-site; USD 80,000 - 110,000; Full time

Job summary

Johnson & Johnson, Inc. is seeking a modeling and analytics professional to expand catastrophe modeling, build a new predictive/statistical capability, and own Qlik/BI reporting for Personal Lines, CPAC, Marketing, and Claims.

You will collaborate with senior leadership, learn across disciplines, and scale the data-platform to support underwriting and pricing strategy in a dynamic environment.

Qualifications

• 0-5 years of experience in insurance, data analysis, or a related analytical field.
• 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.

Responsibilities

• CAT Modeling: Use catastrophe modeling software to analyze risks and support underwriting decisions.
• Predictive Modeling & Statistical Analysis: Develop net-new predictive capabilities and refine pricing models.
• BI/Data Platform (Qlik): Build and maintain Qlik dashboards and data pipelines for multiple business units.
• Data integrity: Ensure data quality across BI tools and data pipelines.
• Cross-functional collaboration: Engage Marketing, Personal Lines, CPAC, and Claims to translate reporting needs into BI solutions.

Skills

Statistical analysis

Data manipulation

SQL

VBA

R

BI tools

Communication

Cross-functional collaboration

Education

Bachelor's degree in Statistics, Mathematics, Risk Management, Data Science, Actuarial Science, or a related field

Tools

Qlik

Tableau

Power BI

Job description

This opportunity is open to all J&J offices, Mount Pleasant preferred.

Base salary range: $80,000.00 - $110,000.00 ( no commission)

MUST be a US citizen to apply.

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.

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.

Requirements

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.