We are looking for a seasoned professional Risk Quant to join our Risk Analytics Methodology team. This role offers the opportunity to work closely with other risk analytics teams, including Market Risk, Credit Risk, SIMM and Quantitative Risk Development teams, to develop tools to support a range of risk management initiatives. The ideal candidate will have strong background and experience in quant finance, financial risk analytics and Python programming.
Key Responsibilities
- Collaborate with end-users to gather requirements and deliver tailored solutions for complex risk analytics workflows across various asset classes, including equity, fixed income, and credit risk.
- Work closely with internal risk teams to design, implement, and ensure consistency of diverse risk measures.
- Develop and implement Python-based tools and libraries to enhance risk analytics processes.
- Develop, maintain, and enhance backend Python libraries to support various risk analytics applications.
- Maintain and improve backend Python libraries to support a range of risk analytics applications.
Required Qualifications
- Education: Bachelor’s or Master’s degree in Quantitative Finance, Mathematics, Computer Science or a related field.
- Experience: At least 3years of professional experience in Python programming on backend development for financial applications.
- Passion for coding and developing innovative solutions with exceptional focus on implementation. Proven ability to develop scalable, reusable Python libraries.
- Strong problem-solving skills and meticulous attention to detail.
- Demonstrates exceptional organizational skills and the ability to independently manage tasks and deadlines
- Proficiency in financial risk analytics and knowledge of market risk and credit risk. Knowledge in regulatory frameworks, including SIMM, is highly desirable.
- Solid understanding of risk modeling and portfolio analytics across various asset classes.
- Excellent communication and collaboration skills, with the ability to work effectively with diverse teams and stakeholders.
Preferred Qualifications
- Knowledge of financial derivatives, portfolio optimization, and risk management practices.
- Ability to handle large datasets and implement efficient processing algorithms.
