Job Description

Equity Risk Quant - VP Level (Convertible Bond Focus)




We are seeking an experienced and highly skilled

Equity Risk Quant

to join our Equity Risk Analytics team at the VP level. This role is specifically tailored for candidates with deep expertise in

convertible bonds

. The successful candidate will play a key role in enhancing our risk analytics capabilities and developing robust tools to support risk management across the equity business.

Key Responsibilities

Lead the design and implementation of risk analytics solutions with a strong focus on

convertible bonds

. Collaborate with Market Risk, Credit Risk, SIMM, and Quantitative Risk Development teams to ensure consistency and accuracy of risk measures across the equity derivatives platform. Partner with trading desks and risk managers to understand complex product structures and deliver tailored risk analytics tools. Develop and maintain Python-based libraries and applications to support real-time and historical risk analysis, scenario generation, and stress testing. Contribute to the enhancement of risk methodologies, including proxy modeling, time series construction, and sensitivity analysis for convertible and structured equity products.

Required Qualifications

Master's or PhD in Quantitative Finance, Mathematics, Physics, Computer Science, or a related field. Minimum of 3 years of hands-on experience as a risk quant, with a strong focus on

convertible bonds

. Deep understanding of equity exotic products, hybrid instruments, and volatility modeling techniques. Proficient in Python, with experience building and maintaining analytical libraries and tools. Strong problem-solving skills, attention to detail, and ability to manage multiple priorities independently. Excellent communication and interpersonal skills, with a collaborative mindset.

Preferred Qualifications

Familiarity with

Leversys

and

Kynex

platforms is a plus. Experience with volatility surface calibration, proxy methodology development, and time series modeling is highly desirable. * Prior exposure to regulatory risk frameworks (e.g., SIMM, FRTB) is advantageous.