Quantitative Research

DESCRIPTION:

Duties: Develop mathematical and statistical models and tools for pricing and risk management of client portfolios and derivative trades.

Utilize factor model and Monte Carlo Simulation techniques to measure and evaluate client portfolios' risk.

Conduct research on client portfolios' risk profiles to identify main risk drivers and monitor firm's risk level.

Formulate and solve large scale portfolio and inventory optimization problems that are subject to various constraints to maximize profit and minimize risk.

Apply time series modeling and machine learning techniques to large-scale data to build prediction models about client behavior / risk metric.

Perform statistical analysis on proprietary data sets to extract signals that can help business identify profitable opportunities.

Implement mathematical and statistical models and data analytics pipelines into firm's development framework.

Monitor ongoing performance of client pricing and risk management models to evaluate their model risk proactively.

Formulate business problems in mathematical terms to be able to solve them analytically.

Collaborate with various stakeholders (Trading, Sales, Risk, Tech, Product Development, etc.) to solve business problems.

Support trading desks and risk functions to help them better serve clients.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Financial Engineering, Mathematics, Statistics or related field of study plus 1 year of experience in the job offered or as Quantitative Research, Quantitative Researcher, or related occupation.

Skills Required: This position requires experience with the following: Building mathematical and statistical models to solve business problems in finance including portfolio construction and optimization, quantifying risk of portfolio using Barra Factor Model, running simulation and extracting signals from financial data to help decision making; applying machine learning techniques including Random Forest and XGBoost to build mathematical models in finance; Conducting feature engineering when building statistical models in finance; Conducting analytical research on equity and equity derivative instruments; software development using C++ and Python in various environments including Windows & Linux; Processing and analyzing big data using Python packages including numpy, pandas, scikit-learn, Keras & tensorflow; Relational database management system language including SQL; Stochastic Calculus and Derivative Pricing; Monte Carlo Simulation; Time Series Analysis including ARMA and GARCH; and Linear Programming Optimization.

Job Location: 383 Madison Ave.

New York, NY 10017.

Full-Time.

Salary: $200,000 - $200,000 per year.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P.

Morgan and Chase brands.

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