Company Overview:

ERNST & YOUNG LLP (EY) is a global leader in assurance, tax, transaction, and advisory services. Operating across diverse industries, including financial services, technology, healthcare, and consumer products, EY helps companies navigate complex business challenges, improve performance, and achieve sustainable growth. With a presence in over 150 countries, EY leverages its extensive network and deep industry knowledge to deliver exceptional client service.

Role Overview:

As an MR Quant within EY, you will be an integral part of a team that develops, validates, and implements sophisticated quantitative models for market risk management.

- You will collaborate closely with clients in the financial services industry, including banks, asset managers, and insurance companies, to address their most pressing risk-related challenges. Your work will directly impact the accuracy and reliability of risk assessments, contributing to the stability and soundness of the financial system.

Key Responsibilities:

- Develop and implement quantitative models for market risk, including Value-at-Risk (VaR), Expected Shortfall (ES), and stress testing, to enhance risk measurement capabilities.

- Validate existing market risk models, ensuring compliance with regulatory requirements and industry best practices, to maintain model integrity.

- Conduct statistical analysis and econometric modeling to identify and quantify market risks, providing insights for risk mitigation strategies.

- Calibrate and backtest derivative pricing models, ensuring accuracy and consistency with market data, to support trading and hedging activities.

- Prepare technical documentation and presentations to communicate model methodologies and results to clients and stakeholders, fostering transparency and understanding.

- Collaborate with cross-functional teams, including risk managers, traders, and IT professionals, to integrate models into risk management systems, improving operational efficiency.

- Stay abreast of the latest developments in quantitative finance and regulatory requirements, contributing to the continuous improvement of risk management practices.

Required Skillset:

- Demonstrated proficiency in quantitative modeling techniques for market risk management.

- Strong understanding of statistical analysis, econometrics, and derivative pricing theory.

- Experience with programming languages such as Python, R, or MATLAB for model development and data analysis.

- Excellent communication and presentation skills, with the ability to explain complex concepts clearly and concisely.

- Ability to work independently and as part of a team in a fast-paced environment.

- A Master's or PhD degree in a quantitative field such as Financial Engineering, Mathematics, Statistics, or Economics.

- 2-7 years of relevant experience in market risk management or quantitative modeling.