Avenir Group
Key Responsibilities:
Assist in identifying and quantifying financial risks through data analysis and quantitative modeling.
Conduct stress tests and scenario analyses to evaluate how different market conditions impact the firms risk exposures.
Develop and implement Python-based risk models and simulations to support risk measurement and management.
Collaborate with senior risk analysts to design and execute stress testing frameworks for various asset classes.
Monitor risk metrics and identify potential risk triggers or emerging risks that could impact the firm's portfolio.
Contribute to the creation of risk reports and presentations to communicate findings to stakeholders.
Stay informed on the latest risk management trends, regulatory requirements, and financial market developments.
Qualifications: Currently pursuing a degree in Quantitative Finance, Financial Engineering, Mathematics, Statistics, Computer Science, or a related field. Experience with risk management software or frameworks such as Value-at-Risk (VaR), Expected Shortfall (ES), or Monte Carlo simulations. Strong proficiency in Python programming, particularly in data manipulation, statistical analysis, and model development using libraries such as NumPy, pandas, and SciPy. Solid understanding of financial risk concepts, including market risk, credit risk, liquidity risk, and operational risk. Knowledge of risk measurement techniques, stress testing, and scenario analysis. Strong analytical and problem-solving skills with the ability to interpret complex financial data. Excellent communication skills with the ability to explain technical concepts clearly and concisely.
Qualifications: Currently pursuing a degree in Quantitative Finance, Financial Engineering, Mathematics, Statistics, Computer Science, or a related field. Experience with risk management software or frameworks such as Value-at-Risk (VaR), Expected Shortfall (ES), or Monte Carlo simulations. Strong proficiency in Python programming, particularly in data manipulation, statistical analysis, and model development using libraries such as NumPy, pandas, and SciPy. Solid understanding of financial risk concepts, including market risk, credit risk, liquidity risk, and operational risk. Knowledge of risk measurement techniques, stress testing, and scenario analysis. Strong analytical and problem-solving skills with the ability to interpret complex financial data. Excellent communication skills with the ability to explain technical concepts clearly and concisely.