Quantitative Research [Multiple Positions Available]

DESCRIPTION:

Duties: Develop and enhance the quantitative modelling, analytics and framework of Value risk management on Value at Risk (VaR), specific risks, stress and regulatory capital.

Implement risk models and business intelligence tools in Python or Excel, conduct ongoing enhancement to current system/infrastructure, design efficient numerical algorithms and implement high performance computing solutions.

Develop and optimize quantitative tools in analyzing profit-and-loss function of SPG products and identify statistical properties of primary drivers behind instruments' valuation.

Perform and analyze back testing for actual portfolios.

Investigate and manage big data sets, conduct research on data integrity, curve construction and backbone analysis with machine learning and traditional statistical models, develop and implement new index for Value at Risk (VaR) methodologies, and automate monthly pool rebalancing.

Document models and communicate with internal model review groups to pass strict company standards.

Explain model behavior to clients and counterparts, carry out scenario analysis, provide guidance and debug analytics.

Lead projects and collaborate with global teams on projects including implementing of new Value at Risk (VaR) framework and methodologies.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Financial Engineering, Computational Mathematics, Computer Science, or related field of study plus two (2) years of experience in the job offered or as Quantitative Research, Risk Analyst, Actuarial Analyst, or related occupation.

The employer will alternatively accept a PhD in Financial Engineering, Computational Mathematics, Computer Science, or related field of study plus One (1) year of experience in the job offered or as Quantitative Research, Risk Analyst, Actuarial Analyst, or related occupation.

Skills Required: This position requires experience with the following: modelling or research with bonds and securitized products; Data extracting and quality analysis on financial market data, such as daily prices, trading volumes and market values, in Excel, SQL, and Python; Data processing and index optimization used in time series rebalancing, construction, and monitoring; VaR, Stress, and FRTB modelling methods; VaR simulation models research, development, and implementation in object-oriented design; Machine learning model research and application in systematic risks, idiosyncratic risks, stress and regulatory capitals; Model performance analysis and visualization in Excel, VBA, and Python; model validation including SR11-7 and model design experience; Statistics including probability theory, regression models, and stochastic processes; Trading desk quantitative support including risk limit monitoring and clean pnl attribution analysis.

Job Location: 270 Park Avenue, New York, NY 10017.

Full-Time.

Salary: $210,000 - $285,000 per year.

JPMorganChase, one of the oldest financial institutions...