Quantitative Research – Rates – Associate

JP Morgan

Location: Greater London

Job Type: Full time

Posted


Quantitative Research (QR) is an expert quantitative modeling group in J.P. Morgan, as well as a leader in financial engineering, data analytics, statistical modeling and portfolio management. As a global team, QR partners with traders, marketers and risk managers across all products and regions, contributes to sales and client interaction, product innovation, valuation and risk management, inventory and portfolio optimization, electronic trading and market making, and appropriate financial risk controls.

Opportunity:

This is an entry level (0-3 years’ experience) quantitative research, analytics, automation and optimization role with the Rates Quantitative Research (QR) AAO at JP Morgan. The role affords the new team member opportunities to work on the cutting-edge data analytics and quantitative Rates and CEM (Currencies and Emerging Markets) trading optimization problems. The team's mission is to bring data-driven decision making and automation to the Rates & CEM business.

Core Responsibilities:

  • Develop and maintain models, methodologies and infrastructure to provide quantitative inputs to the algorithmic and systematic trading strategies in Rates
  • Work across Rates Derivatives quantitative modeling and automated trading strategies in establishing the common grounds and approaches in building new models and execution algorithms
  • Enrich Rates Derivatives modeling with the latest state-of-the art Data Analytics, Artificial Intelligence and Machine Learning models, approaches and techniques.
  • Develop data-driven decision making analytics with demonstrable impact

Essentialskills, experience, and qualifications:

  • PhD, MS or equivalent degree from top tier schools / programs in Mathematics, Mathematical Finance, Statistics, Physics, or Engineering
  • Excellence in probability theory, numerical analysis and Machine Learning techniques
  • Strong analytical skills, knowledge of Statistical Learning and its applications to Finance
  • Strong software development; Python and C++ skills
  • Preferable: knowledge of Financial Engineering and Rates financial products
  • Excellent communication skills, both oral and written
You’ve got this!