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Consultant ERM Risk Modeling
Ref No.: 19-07208
Location: Columbus, Ohio
Role Summary
This position will have responsibility for several key areas of Enterprise Model Risk Management (MRM) capabilities, including providing support for independent model validation and governance, MRM framework tools, third-party interactions, and MRM reporting capabilities. This individual will have focused responsibility toward advanced data analytics. This individual will serve as the local data science expert in validating models and providing advisory consultation to model owners.
Key Responsibilities

(50%) – Independent model validation and governance – support the process to inventory enterprise models, and ensure policy compliance with Enterprise Model Risk Management Policy and Procedures documents, including conducting independent model validations for critical models. Support the process to ensure model risk management and oversight are in compliance with internal and external best practices. Plans and manages the execution of model validations, participates in planning including defining project scope, schedule, resource requirements, and delivery timelines. Applies appropriate quantitative techniques and methods to conduct tests and evaluate client models. Responsible for performing analysis using statistical, database, and/or general programming languages and tools. Support the process of the model risk monitoring and converged issue management. Support model owners in issue planning and mitigation.

(30%) – Consulting and Training – support model risk management team and model owners with advanced data analytics. Provide consultation and trainings on statistical modeling, machine learning and artificial intelligence. Keep up with industry development in data science.

(10%) – MRM Framework Tools – support the development of the existing enterprise model inventory, and MRM's risk and control assessments that are administered through GRC tool, OpenPages.

(10%) – Third-Party Interactions – support interactions with rating agencies, regulators, consultations with business units and Internal Audit, and the Model Risk Management Committee (MRMC).

Education/Certifications/Licenses:
Strong technical and quantitative capabilities, including key certifications, are strongly preferred. Certifications may include FCAS, ACAS, FSA, ASA, CQF, CFA, CRM, Client, QRM, or other risk and or financial analysis designations. Candidates with advanced degrees, including Statistics, are preferred.

Experience/Skills:
• Proven experience building practical solutions using predictive modeling. Demonstrated knowledge of and experience with design of experiments.
• Possesses core statistics skills including an understanding of probability and its application to the analysis of data. Able to evaluate sources of variation and identify influential factors/features. Experienced with statistical process control, process monitoring and diagnostics.
• Modeling and Machine Learning: Experienced with advanced mathematical modeling techniques including both supervised and unsupervised learning algorithms.
• Ability to understand business systems (processes) and the data produced by them – (how did the data get produced and is it a valid representation of the outcome being studied). Demonstrated experience structuring and solving complex business problems.
• Ability to translate analytic findings into actionable communications. Ability to communicate effectively in a variety of mediums with any audience. Capable of developing compelling stories and distinctive data visualizations
• Working knowledge of statistical software including R, SAS, SPSS, MatLab, etc. as well as Teradata, Oracle, DB2, SQL Server, Netezza, etc. Understands data structures operational vs analytical data structures, normalization, etc. and SQL Assistant, WinSQL, and Toad, etc. Knowledge of general purpose programming languages (Python, Java, C++, etc) including domain specific languages, static and dynamic languages, application design and development, test driven development, and agile practices.

Job Conditions
Overtime Eligibility: Not Eligible (Exempt)

RELATIONSHIP: Reports to Sr. Consultant, AVP or VP Enterprise Risk Management. Typically does not have direct reports but may manage several Analysts and Specialists on special projects/studies. May be responsible for matrix reporting relationships or virtual teams.
JOB RESPONSIBILITIES: Enterprise risk management consultants who focus on risk modeling apply theoretically sound methodologies to model various risks inherent in order to form a holistic view on capital position for economic, rating agency, regulatory, and accounting (GAAP/STAT) perspectives. Incumbents will use stochastic models for applications such as strategic asset allocation, pricing, reinsurance, and others.

1. Assesses the methodologies and assumptions used for economic capital modeling.

2. Assesses modeling infrastructure and suitability for risk management processes.

3. Creates/parameterizes modeling tools to update various risk metrics. Conduct sensitivity tests on these models.

4. Evaluates capital position using risk models. Produces associated probability distributions from the perspective of different stakeholders.

5. Analyzes scenarios generated by risk models, identify key risks, and monitor the trend of those metrics.

6. Drives the use of economic capital concepts such as REC and RAROC within and across business units when appraising financial performance and pricing business.

7. Provides internal customers with the appropriate frameworks and tools to manage their business on a risk adjusted or risk informed basis.

8. Plans and oversee the preparation of risk models. Reports, presents, and communicates the results of the economic capital models.

9. Educates business partners on enterprise risk management and risk and capital models. Performs other related duties as assigned.

JOB REQUIREMENTS:

Education: Undergraduate studies in statistics, actuarial science, or related discipline. Master's degree in statistics, economics, actuarial science, or MBA in Finance preferred.

Designations: FCAS, ACAS, or CFA a plus.

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

Knowledge: Proven knowledge in risk management and the insurance industry. Solid understanding of stochastic processes, Monte Carlo simulations, and other statistical techniques applicable to risk modeling. Technical understanding of asset-liability management, portfolio management, reserving, and pricing.

Skills/Competencies: Advanced communication skills for verbal and written contact with Finance and Business Unit leadership. Ability to communicate technical concepts to all levels of associates and leadership.

Presentation skills. Ability to use Excel and statistical software such as SAS or Matlab to develop cost-effective processes to assess and monitor complex risks inherent in insurance business.

Values: Regularly and consistently demonstrates the *** Values and Guiding Behaviors.

Staffing Exceptions to the above minimum job requirements must be approved by the CFO, or the HR Leader.

JOB CONDITIONS:

Overtime Eligibility: Not Eligible (Exempt).

Working Conditions: Normal office environment.

ADA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.

Job Evaluation Activity: Evaluated August 2009 KCP/SO