Principal Solutions Architect - Cary, United States - SAS

SAS Cary, United States

2 weeks ago

Description

Summary of Duties: Play principal role in development and implementation of the risk content, as well as assessment and assimilation (where appropriate) of the field and project developed assets. Develop and enhance quantitative tools and models in analyzing profit-and-loss function of financial products, and statistical properties of instruments' price drivers. Document modeling choices and corresponding statistical analysis. Assess and where appropriate bring in field-developed modeling content. Create and support use cases to show specific business applications of the models. Publish academic research and present specific, relevant content at conferences. Develop on-going testing regimens to ensure that the models behave according to expectations through time. Deliver on all phases of model development, from design through training, testing, validation, and implementation. Engage with stakeholders to obtain requirements and set milestones to update on the model development progress in a periodic manner. May work remotely pursuant to SAS Flexible Work Policy.

Qualifications: Position requires a Masters degree in Finance, Engineering, Mathematics, Physics, Computer Science or a related quantitative field of study plus five (5) years of experience in the job offered or five (5) years of experience as a Quantitative Analyst, Risk Modeling Researcher, Research Assistant Professor, Postdoctoral Fellow, or a related occupation. Alternatively, the employer will accept a PhD degree in Finance, Engineering, Mathematics, Physics, Computer Science or a related quantitative field of study, or a related field plus two (2) years of experience in the job offered or two (2) years as a Quantitative Analyst, Risk Modeling Researcher, Research Assistant Professor, Postdoctoral Fellow, or a related occupation.

Requires experience with advanced mathematics arising in financial modeling, such as probability theory, time series analysis, or statistics. Requires advanced quantitative skills in: Numerical Methods, Stochastic Calculus/Probability and Random Processes, Martingale Methods in arbitrage pricing, and Statistics/Time Series Analysis. Requires practical data analytics skills, gained through hands-on experience, on real data sets, including familiarity with methods for working with large data and tools for data analysis. Requires strong technical skills. Requires proficiency in a computational language such as C++, Python or R. Requires extensive experience with analyzing large and complex data sets. Requires practical knowledge of financial products, their pay-off functions, and modeling. Requires thorough understanding of interest rate modeling.

Additional Information:

To qualify, applicants must be legally authorized to work in the United States, and should not require, now or in the future, sponsorship for employment visa status. SAS is an equal opportunity/Affirmative Action employer. All qualified applicants are considered for employment without regard to race, color, religion, gender, sexual orientation, gender identity, age, national origin, disability status, protected veteran status or any other characteristic protected by law. Read more: Know Your Rights. Also view the Pay Transparency notice.

Resumes may be considered in the order they are received. SAS employees performing certain job functions may require access to technology or software subject to export or import regulations. To comply with these regulations, SAS may obtain nationality or citizenship information from applicants for employment. SAS collects this information solely for trade law compliance purposes and does not use it to discriminate unfairly in the hiring process.

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