Quantitative Research [Multiple Positions Available]

JPMorgan Chase & Co.•Jersey City, NJ

4h•$210,000 - $285,000•Onsite

About The Position

Duties: Guide cross-functional teams in strategic initiatives to enhance product innovation, optimize valuation techniques, and implement advanced risk management strategies across global markets. Architect and deploy risk analytics platforms, focusing on real-time data integration, advanced model performance assessment, and dynamic P&L attribution. Pioneer the optimization of analytics algorithms, utilizing machine learning and artificial intelligence to enhance the accuracy and scalability of financial models. Design and implement computing solutions, enabling processing of financial data and enhancing computational capabilities. Establish a model risk governance framework, conducting rigorous evaluations of quantitative models, identifying potential limitations, and implementing robust risk mitigation strategies. Drive initiatives to ensure compliance with evolving regulatory requirements, while fostering a culture of innovation and continuous improvement in financial analytics. Spearhead the development of financial engineering solutions, leveraging advanced data analytics and statistical modeling to ensure business growth and stability. Develop and integrate software frameworks for analytics, ensuring seamless delivery and integration with enterprise systems and applications, and driving innovation in financial technology.

Requirements

Master's degree in Finance, Financial Engineering, Economics, Statistics, Mathematics, or related field of study plus 3 years (36 months) of experience in the job offered or as Quantitative Research Associate or related occupation. The employer will alternatively accept a Bachelor's degree in Finance, Financial Engineering, Economics, Statistics, Mathematics, or related field of study plus 5 years (60 months) of experience in the job offered or as Quantitative Research Associate or related occupation.
Manipulating and analyzing data Python and C++
Using libraries including Numpy, Scipy, and Pandas
Processing data sets using data containers, multithreading, and multiprocessing in PySpark and Tensorflow
Developing robust financial software solutions using data structures, standard algorithms, and Object-Oriented Programming
Creating financial quantitative analysis tools that deploy as REST APIs utilizing data structures, algorithms, and Object-Oriented Programming design principles
Developing financial quantitative analysis frameworks using React, Spark, JavaScript, TypeScript, and SQL
Applying mathematical and statistical techniques to real-world financial problems
Implementing and optimizing machine learning models for financial applications
Modeling and valuing financial instruments, financial products, and derivatives valuation models, using probability theory, financial mathematics, and stochastic calculus
Analyzing the pricing of financial instruments including bonds, equities, loans, mortgages, securitized products, and interest rate swaps and their valuation.

Responsibilities

Guide cross-functional teams in strategic initiatives to enhance product innovation.
Optimize valuation techniques.
Implement advanced risk management strategies across global markets.
Architect and deploy risk analytics platforms.
Focus on real-time data integration, advanced model performance assessment, and dynamic P&L attribution.
Pioneer the optimization of analytics algorithms, utilizing machine learning and artificial intelligence to enhance the accuracy and scalability of financial models.
Design and implement computing solutions, enabling processing of financial data and enhancing computational capabilities.
Establish a model risk governance framework, conducting rigorous evaluations of quantitative models, identifying potential limitations, and implementing robust risk mitigation strategies.
Drive initiatives to ensure compliance with evolving regulatory requirements, while fostering a culture of innovation and continuous improvement in financial analytics.
Spearhead the development of financial engineering solutions, leveraging advanced data analytics and statistical modeling to ensure business growth and stability.
Develop and integrate software frameworks for analytics, ensuring seamless delivery and integration with enterprise systems and applications, and driving innovation in financial technology.