Sr Consultant, Risk Analytics

As a team member in the Finance and Internal Audit department at Nationwide, the opportunities are endless! You can grow and learn in diverse areas across many disciplines such as Advanced Analytics, Investments, Actuarial, Accounting, Risk Management, Critical Business Advisor and so much more. 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.

This role does not qualify for employer-sponsored work authorization.  Nationwide does not participate in the Stem OPT Extension program.

Internal Compensation Grade: H5
Location: This position can be filled as Hybrid in Columbus, OH

Job Description Summary

Do you have the desire to play a critical role in driving data-based business outcomes? Nationwide has been using data to serve our members and drive business outcomes for almost 100 years. Our industry-leading workforce accepts an agile work environment and a collaborative culture to deliver outstanding solutions and results. Our Risk Analytics professionals play a key role in transforming quantitative data analysis into meaningful insights that drive business results. Specifically, they serve as the conduit joining quantitative risk analysts to business partners.

As a Senior Consultant, you’ll be responsible for the creation and management of risk analytics projects to solve business problems and objectives. You’ll work strategically and consultatively with business partners across the organization to match quantitative analysis with business needs. We’ll count on you to be the key point of contact, linking business to technical research. It’s imperative that you have both a confirmed understanding of quantitative analytics and that you are able to expertly articulate solutions to many levels of leadership.

Job Description

Key Responsibilities:

• Understands and assesses key business needs. Proactively owns the strategic development of appropriate quantitative modeling solutions.

• Collaborates with organizational departments or business functions to accomplish strategic goals, objectives, and initiatives.

• Builds risk analytic strategies for business problems through collaborating, consulting and driving expectations.

• Leads in the understanding and analysis of models across the enterprise to ensure that model assumptions, processes and outputs are well understood and that modeling standard methodologies are upheld.

• Crafts clear and concise summaries of findings and recommendations. Uses impactful storylines and data visualization geared to both technical and non-technical audiences.

• Drives business value through crafting and communicating strategic business solutions to leaders. 

• Leads all aspects of development, testing, implementation and administration of quantitative modeling processes and tools.

• Evaluates and ranks quantitative solutions to business problems.

• Leads communication of the key benefits and limitations of sophisticated modeling tools for business applications.

• Leads governance of modeling tools and ensures they are applied consistently. 

May perform other responsibilities as assigned. 

Reporting Relationships: Reports to Risk/Actuarial leader. 

Typical Skills and Experiences: 

Education: Undergraduate studies in finance, accounting, economics, statistics, mathematics or related subject area required. Graduate-level studies in a related field with advanced degree highly desirable. 

License/Certification/Designation: Progress toward FCAS, FSA, CQF, CFA or similar preferred.

Experience: Typically, seven or more years of related work experience in financial risk modeling or actuarial functions. 

Knowledge, Abilities and Skills: Proven knowledge of processes and functions spanning the insurance and risk management cycle. Understands machine learning, stochastic processes, Monte Carlo simulations, sampling methods and other statistical techniques applicable to specialized risk modeling. Confirmed mathematical knowledge of specialized risk