For more than 140 years, Prudential has delivered products and services that help address the financial challenges of individual and institutional customers. Today, with operations in the United States, Asia, Europe and Latin America, Prudential is among the world’s largest financial services companies. Building your career at Prudential offers you the opportunity to truly make a difference.
This position will be part of the Model Risk & Analytics Audit team, primarily responsible for independent model reviews and testing of models, end user computing solutions, and advanced analytics (Artificial Intelligence (AI), Machine Learning (ML)).
This individual will collaborate with our Financial, Actuarial, Investments, Risk (FAIR) audit partners and will play a key role in developing best-in-class solutions to support audit executions, reporting and analytic capabilities leveraging both internal and external data.Primary Responsibilities
- Assess the design and implementation of model risk frameworks through targeted first line and second line model related audits.
- Evaluate the effectiveness and quality of model risk mitigation controls (including first line Model Development Life Cycle (MDLC) and second line model validation).
- Assess current key modeling and end user computing processes for potential improvements to enhance modeling/ analytical capabilities and efficiency.
- Participate in a cross functional team throughout the MDLC to assist in the development, implementation (testing), use, performance monitoring and review of modeling technology solutions. This will include those solutions associated with the implementation of key enterprise initiatives including CECL, FASB TI methodology, and Libor transition, to name a few.
- Contribute to the development of tools and solutions for modeling capabilities.
- Develop knowledge of data and model governance concepts that ensures consistency and integrity in model intended uses through the review of model documentation, influential test plans, and technical coverage of modeling capabilities.
- Research evolving techniques, regulatory requirements and emerging modeling risks of advanced analytics (AI, ML).
- Gain exposure to, and develop an in-depth understanding of, multiple lines of business and model types: pricing, financial reporting, capital, forecasting and stress testing.
- M.S. or B.A. Degree required in Actuarial Science, Financial Engineering, Mathematical Finance, Applied Mathematics, Statistics, or related analytical fields.
- Excellent mathematical, analytical problem-solving skills. Risk management or actuarial credential (e.g. FRM, FSA, CERA, ASA) is a plus .
- Effective communication (both written and oral) skills, including the ability to communicate technical concepts to non-technical colleagues.
- Strong relationship and expectation management skills, ability to collaborate with individuals with various expertise and backgrounds.
- Highly curious, motivated and innovative problem solver and conceptual thinker.
- Experience in model development, implementation and/or validation is a plus.
- Knowledge of analytical software packages, such as MATLAB, R, Python is desirable.
- Experience with data validation and reconciliation, database development and maintenance, data governance and reporting is desirable.
- Experience in financial services industry (bank, insurance company, hedge fund, etc.) with knowledge of insurance or bank products is a plus.
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