Role Description
As a team member in Finance at Nationwide, a Fortune 100 company with nearly $70 billion in annual sales, the opportunities are endless! Let Nationwide help create your career journey! At Nationwide®, “on your side” goes beyond just words. Our customers are at the center of everything we do and we’re looking for associates who are passionate about delivering extraordinary care.
Sr Actuarial Associate, Enterprise Catastrophe Risk
Nationwide’s Catastrophe Risk Modeling team serves as a specialized enterprise capability focused on understanding and quantifying catastrophe exposure across physical property portfolios and weather-related risk scenarios. The team combines catastrophe analytics, actuarial analysis, and risk modeling to help the business better understand risk and support more informed decisions across the enterprise.
This role will help strengthen how catastrophe-related models and analyses are developed, validated, and interpreted so the team can produce high-quality analytics and more actionable insight for business partners. This is a compelling fit for someone who likes hands-on analytical work, enjoys solving modeling and analytical challenges, and wants to contribute to a team that turns complex risk data into meaningful business value.
Key Responsibilities
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Support catastrophe risk research, actuarial analysis, and model development tied to physical property, weather, and catastrophe exposure data.
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Build, enhance, and validate catastrophe risk models and analytical processes that support research, modeling, and reporting use cases.
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Use tools such as SQL, Python, R, Databricks, and Snowflake to support actuarial analysis, model development, validation, and reporting.
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Support model validation and reporting workflows that help ensure outputs are accurate, consistent, and decision-useful.
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Contribute to model improvement and process automation efforts that make catastrophe analytics more efficient, scalable, and impactful.
Qualifications
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Bachelor’s degree in a quantitative field such as data science, statistics, mathematics, actuarial science, computer science, engineering, finance, or a related discipline.
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ACAS level actuary credential required; additional progress toward FCAS credential preferred.
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Previous professional experience in P&C pricing or reserving position (catastrophe modeling specific experience highly preferred).
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Strong SQL capability and working proficiency in Python and/or R.
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A naturally curious, detail-oriented approach, with the judgment to question results, investigate discrepancies, assess model reasonableness, and improve the quality of outputs.
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This role does not qualify for employer sponsored work authorization. Nationwide does not participate in the STEM OPT extension program.
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It is our intention to fill this role in Columbus, OH. However, applications from candidates working remotely who bring critical industry skills and relevant experience may be considered.
Requirements
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Typically, seven or more years of related work experience in financial risk modeling or actuarial functions.
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Strong understanding of machine learning, stochastic processes, Monte Carlo simulations, sampling methods and other statistical techniques applicable to specialized risk modeling.
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Proven mathematical knowledge of specialized risk models such as those used in hedging, economic scenario generation, catastrophe, credit risk, etc.
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Advanced understanding of risk management operations such as asset-liability management, portfolio risk assessment, hedging, etc.
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Sophisticated written and verbal communication skills.
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Advanced proficiency with Excel and common statistical software such as R, SAS, Python, or MATLAB.
Benefits
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Medical/dental/vision.
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Life insurance, short and long term disability coverage.
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Paid time off with newly hired associates receiving a minimum of 18 days paid time off each full calendar year pro-rated quarterly based on hire date.
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Nine paid holidays.
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8 hours of Lifetime paid time off.
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8 hours of Unity Day paid time off.
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401(k) with company match.
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Company-paid pension plan.
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Business casual attire.
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And more.