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Quantitative Trading & Research – Prime Finance Service – Associate
mid · Technology / Software Development
Quantitative Trading Research (QTR) is a global team which expertise ranges across various fields: Derivatives Modelling, Financial Engineering, Data Science and Quantitative Development. We provide quantitative expertise and diverse product offerings to clients. As part of the global QR Group, you'll work on unique analytics and mathematical models, transforming business practices through automation and quantitative methods where JP Morgan is a dominant player.
Job summary:
As an Analyst or Associate Quantitative Researcher in the Quantitative Trading & Research (QTR) Prime Finance Service (PFS) team, you’ll will be mainly contributing to the FnO and OTC derivatives risk and margin agenda for QTR PFS. Additionally, you’ll contribute to the strategic agenda to transform our investment bank into a data-led business and encourage change using state-of-the-art machine learning techniques. Specially, you’ll have the chance to
Job responsibilities
Develop/improve mathematical models for pricing and risk/margin measurement for multi-asset FnO/OTC derivatives. Support intraday and EOD pricing, risk/margin and PnL calculation.
Support the desk and provide portfolio risk management solutions by explaining model behavior, identifying major sources of risk in portfolios, carrying out scenario analyses, developing and delivering quantitative tools.
Develop and deliver analytics that help transforming the business and contributing to the automation agenda. • Partner with Technology and Prod Dev to deliver QTR analytics to the business.
Drive projects end-to-end, from brainstorming and prototyping to production delivery.
Develop and deliver ML/AI models and end-to-end solutions.
Contribute to EOD or intraday hedging activities and algo design.
Required qualifications, capabilities, and skills
Advanced degree (PhD, MSc or equivalent) in Mathematics, Physics or Computer Science.
Knowledge of the FnO/OTC derivatives products and good understanding of risk/PnL and Margin methodology and demonstrate quantitative and problem-solving skills.
Strong coding skills (Primarily Python or C++), proficiency in code design and can navigate large libraries and quickly debug complex logics.
Experience in a trading desk support position either as a quant or a developer.
Excellent communication skills, both verbal and written, can engage and influence partners and business/non-Tech stakeholders and enthusiastic about knowledge sharing and collaboration.
Detail-oriented and can work on adhoc requests and can sometimes work under pressure
Preferred qualifications, capabilities, and skills
Knowledge of curve building, volatility surface calibrations and more.
Knowledge of market risk, time-series analysis, VaR and Stress
Knowledge of ML algorithms and experience in delivering AI models / end-to-end solutions
Knowledge of Optimization and hedging algorithms