London

Responsiblities 

• Assist a Portfolio manager in identifying and evaluating risk factors across multiple Equity based strategies
• Develop statistical factor models to assess the current market stress and monitor the risk level of the current positions
• Assist in the enhancement and support of existing risk systems and applications (Valuation, Risk, Pnl Predict, Pnl Explain, Scenario Analysis)
• Developt tools for interacting with various internal systems
• Apply statistical/ machine learning techniques (multilinear regressions, time series analysis) to identify trends, patterns, and relationhips in data
• Develop novel visulations using (matplotlib, seaborn, bokeh, etc) for Risk Managers to better understand sources of market risk
• Clean and validate output data
• Gather historical data on risk factors for analysis
• Writing Python scripts to automate tasks

Qualifications 

• Pursuing a Graduate’s Degree in Financial Engineering
• Interest in financial markets
• Deep understanding of Regression based models
• Ability to manipulate large dataset
• Experience in writing Python code (Pandas, numpy, sklearn)
• Strong communication skills both written and verbal
• Ability to find creative solutions to problems