Sr. Quantitative Engineer (SAS, R Programming, Financial Analytics)
3900 Wisconsin Ave Washington, District Of Columbia 20016
Kavaliro has an immediate need for a Sr. Quantitative Engineer with experience of quantitative financial analytics (preferably in mortgage credit risk analytics) using SAS and R Programming. Use advanced computational, mathematical, and statistical or data analysis tools to implement and test financial modeling and analytical software systems for use in product development, portfolio management, forecasting, risk management and other business applications.
- Bachelor degree in Computer Science, Computer Engineering, Math/Statistics, Finance/Economics, Physics or related engineering/quantitative fields.
- Master or PhD degree preferred.
- 4+ years’ experience in coding advanced modeling concepts and mathematical equations.
- Proficient in SAS and experienced with R. Knowledge of relational Databases/SQL required.
- Knowledge/experience of quantitative financial analytics (preferably in mortgage credit risk analytics) a plus.
- Experience in software development process required, Agile experiences a plus.
- Excellent written and verbal communication skills. Familiar with tools like Microsoft office suites and JIRA.
- Experience in working on internal pricing or loss forecast applications a plus.
Key Job Functions
- Under general direction of supervisor, develop and implement all components of financial models, cash flow simulations and risk metrics calculations in end-user or production computing systems for use in business decisions, financial and regulatory reporting, and risk management.
- Translate complex mathematical, business, and financial modeling logic into software code, with minimal supervision.
- Design and execute test cases for modeling and analytical software applications to ensure they meet business needs and model requirements.
- Assess model implementation quality and production control risk, with minimal supervision.
- Execute model application runs, process/validate model outputs, and produce/review quantitative reports for business use.
- Apply emerging technologies and industry best practices of model and analytical system implementation.
- Communicate complex quantitative analysis in a clear, precise and actionable manner both verbally and in writing.
- Work and collaborate effectively, as part of a team and across organizational lines.