Quantitative Research-Modelling -Vice President
JP Morgan
5 - 10 years
Mumbai
Posted: 12/6/2024
Job Description
Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? As a Quantitative Modeler within the Quantitative Research team at J.P. Morgan, you will play a pivotal role in shaping our firm's future and will provide effective, timely, and independent assessments of our booking models and contribute to the development of alternative benchmarking models.
Join our dynamic and growing Quantitative Research team at J.P. Morgan as a Quantitative Modeler. This role offers the chance to shape our firm's future by providing independent assessments of our booking models and developing alternative benchmarking models. You'll have the opportunity to leverage your experience in designing independent valuation applications, making a significant impact on our team. Our global team is a leader in financial engineering, data analytics, statistical modeling, and portfolio management, partnering with various stakeholders across all products and regions.
Job Responsibilities:
- Define the architecture for a state-of-the-art model calibration and independent valuation application that is modular, scalable and robust
- Integrate and develop mathematical models for the calculation of pricing adjustments, model limitation provisions, model parameter uncertainty reserves and other regulatory calculations like prudential valuation adjustments and CCAR stresses
- Drive initiatives for increased automation and digitization across the model space, including inventories of models, products, limitations and adjustments
- Design and implement data pipelines for the ingestion, processing and storage of independent datasets used for model calibration and build analytics to remediate model limitations identified by the model validation team to better manage the model risk appetite of the firm
- Optimize the application for high performance utilizing distributed computing, cloud-based solutions, or GPU acceleration where possible
- Design and develop software frameworks for analytics and their delivery to downstream systems and application
Required qualifications, capabilities and skills:
- You demonstrate quantitative and problem-solving skills as well as research skills
- You demonstrate proficiency in software design patterns, code design and programming skills, with primary focus on Python and C++;
- You have practical experience with code performance optimization, debugging and reverse engineering
- You understand advanced mathematics arising in financial modeling, such as probability theory, stochastic calculus, statistics etc.
- You have hands-on experience with data analytics, including working with large data sets and tools for data analysis and visualization.
- You have excellent verbal and written communication and team skills in a multi-location set-up
Preferred qualifications, capabilities and skills:
- Advanced degree (PhD, MSc or equivalent) in Computer Science, Engineering, Mathematics, Physics, etc.
- Markets experience and familiarity with general trading concepts and terminology
- Knowledge of options pricing theory, trading algorithms, financial regulations, stochastic process, partial differential equations and numerical analysis
- Knowledge of financial products, their payoff functions and models
- Familiarity with full-stack software development
About Company
JP Morgan Chase & Co. is one of the world's largest and most prestigious financial institutions, headquartered in New York City. It operates in over 100 countries, providing a wide range of financial services including investment banking, asset management, commercial banking, and wealth management.The company serves corporations, governments, institutions, and individual clients, offering expertise in areas such as mergers and acquisitions (M&A), securities trading, and credit management. Known for its global reach and financial strength, JP Morgan is a leader in innovation and sustainability within the banking industry.
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