At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. As a Quantitative Analytics & Model Development Professional within PNC's Risk Management organization, you will be based in Pittsburgh, PA.
The PNC Financial Services Group, Inc. seeks a Quantitative Analytics & Model Development Professional in Pittsburgh, PA. Within the Market Risk Management department, perform advanced quantitative analyses and/or model/tool development to support business decision-making or risk management, as well as document analyses and results appropriately and support internal/external communications. Specific duties include: (i) support the line of business by analyzing and developing new model/tool frameworks; (ii) refine, monitor, review and/or validate existing models/tools; (iii) work with large and/or complex datasets to create or test models/tools; (iv) perform quantitative analysis and develop reports; (v) perform qualitative and quantitative assessments of all aspects of models or quantitative tools including theoretical aspects, model design and implementation as well as data quality and integrity; (vi) analyze complex data and associated quantitative analysis and summarize results; (vii) make recommendations based on findings from data analytics; (viii) use quantitative tools and techniques to measure and analyze model risks; (ix) evaluate identified model risks and reach conclusions on strengths and limitations of the model; (x) conduct on-going communication with model stakeholders such as developers, owners and reviewers; and (xi) prepare detailed documents on quantitative models/tools for internal/external communications and/or regulatory compliance, using applicable templates.
Master’s degree in Computational Finance, Mathematical Finance, Economics, Mathematics, or Statistics plus 1 year of experience in a position requiring quantitative modeling and documentation is required. Additional requirements include: (i) one year of academic or industry experience in probability theory, linear algebra, derivation of partial differential equations, application of numerical analysis, finite difference methods on differential equations, optimization theory, and stochastic differential equations; (ii) experience defending Master’s or Ph.D. thesis and authoring peer-reviewed scientific research papers suitable for independent review; (iii) knowledge of the valuation of financial derivatives, Black-Scholes models, Greeks, Ito’s Lemma, interest rate term structure modeling; and (iv) experience with programming skills in Matlab and Excel VBA.
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