***We are unable to sponsor for this permanent full-time role***
***Position is bonus eligible***
Prestigious Financial Institution is currently seeking a Senior Quantitative Risk Analyst. Candidate is responsible for one or more functions within Quantitative Risk Management (QRM) to develop and maintain model analytics and performance monitoring. The Associate Principal will collaborate with other quantitative analysts, business users, data & technology staff, and model validation colleagues to implement new analytics and enhance existing tools.
- To perform this job successfully, an individual must be able to perform each assigned essential duty satisfactorily:
- Maintain and build data models to ensure information is available in our analytics warehouse for downstream uses, such as analysis and dashboard development
- Perform model performance testing, including portfolio back-testing using historical data.
- Support the launch of new products by enhancing monitoring capabilities.
- Create documentation and testing to ensure data is accurate and easily understandable
- Discover and share best practices for data and analytics engineering with members of the team
- Invest in your continued learning on data and analytics engineering best practices and evaluate them for fit in improving maintainability and reliability of analytics infrastructure
- Assist analysts in solving their analytics questions/challenges
- Strong programing skills. Able to read and/or write Python code in a collaborative software development setting.
- Experience with Tableau and Alteryx
- Experience with a source code repository system (preferably Git)
- Ability to write and optimize complex analytical (SELECT) SQL queries
- Ability to collaborate with multiple partners (e.g., DBAs, Data Architecture, Security) to craft solutions that align business goals with internal security and development standards
- Comfortable supporting business analysts on high-priority projects.
- High attention to detail and ability to think structurally about a solution
- Strong problem-solving skills: Be able to accurately identify a problem's source, severity, and impact to determine possible solutions and needed resources.
- Strong quantitative skills, ability to demonstrate deep understanding in the following technical areas:
- Financial mathematics (derivatives pricing models, stochastic calculus, statistics and probability theory, advanced linear algebra)
- Econometrics, data analysis (e.g., time series analysis, GARCH, fat-tailed distributions, copula, etc.) and machine learning techniques
- Numerical methods and optimization; Monte Carlo simulation and finite difference techniques
- Risk management methods (value-at-risk, expected shortfall, stress testing, back-testing, scenario analysis)
- Financial products knowledge: good understanding of markets and financial derivatives in equities, interest rate, and commodity products.
- [Preferred] Model development and prototyping requires advanced development skills in Python and database manipulation.
- [Preferred] Model implementation requires advanced Java programming ability and a demonstrated ability in developing and maintaining enterprise level software.
- [Preferred] Ability to challenge model methodologies, model assumptions, and validation approach.
- [Preferred] Proficiency in technical and scientific documentation (e.g., white papers, user guides, etc.).
- [Preferred] Experience in Agile/SCRUM framework.
- [Required] Experience with Tableau and Alteryx
- [Required] Experience in a scripting language such as Python is required.
- [Required] Experience in office technology such as PowerPoint, Confluence, Latex, Word, and Excel.
- [Required] Experience with code repository, build and deployment tools (e.g., Git, GitHub, Jenkins
Education and/or Experience:
- Master’s degree or equivalent in a quantitative field such as data analytics, computer science, mathematics, physics, finance/financial engineering. PhD preferred.
- Two to seven years of experience in data analytics required
- Experience in areas in finance and/or development experience in model implementation and testing.
- FRM, CFA, etc., are desirable, but not required.