Quant Analyst

LSEG•Boston, MA

2d•$78,200 - $130,400•Onsite

About The Position

This position is within the Quantitative Services team of LSEG’s Post Trade Solutions division in Boston. The team develops the Open-Source Risk Engine (ORE) and its dependent services, and implements ORE at major financial institutions to provide transparent, state-of-the-art risk management. The successful candidate will work with a team of quants to develop solutions for risk analytics services. Applicants must be in the penultimate year of graduate study and due to complete their degree on or before summer 2027. They should be pursuing a predicted PhD or master’s degree in mathematics, physics, financial engineering, or another quantitative field.

Requirements

Be in the penultimate year of graduate study and due to complete the degree on or before summer 2027.
Have a predicted PhD or master’s degree in mathematics, physics, financial engineering, or another quantitative field.
Demonstrate an interest in quantitative finance through studies, projects, or independent work.
Have a good understanding of at least one of Python or C++.
Have functional knowledge of stochastic models and stochastic differential equations, such as Ornstein-Uhlenbeck/Hull-White or Black-Scholes models.
Be able to collaborate with others and communicate effectively.
Show curiosity about data and an ability to analyze information, draw conclusions, and propose solutions.
Have knowledge of financial derivatives and pricing techniques, such as finite difference methods or Monte Carlo simulation.

Nice To Haves

Familiarity with Git and LaTeX is ideal but not essential.

Responsibilities

Contribute to the development of the Open-Source Risk Engine (ORE).
Support the infrastructure for the IM Risk Generation (IMRG) service.
Price client portfolios and perform stress-testing and backtesting using ORE.
Use ORE to calculate portfolio risk, including VaR and SIMM.
Translate client portfolios into ORE XML format.
Collaborate with collateral management and risk teams to build financial applications.