Flag job

Report

2025 Risk Management Off-Cycle Internship - Quantitative

Min Experience

0 years

Location

Frankfurt, Germany

JobType

internship

About the job

Info This job is sourced from a job board

About the role

This Internship is an opportunity to experience the culture and atmosphere in the Firm Risk Management Division by taking on some of the responsibilities and functions of a Full-time Analyst for a short period. The internship typically lasts six to twelve months but can vary in length depending on business needs and candidate availability. This is a part-time internship (up to 20hr a week). The cornerstone of Morgan Stanley's risk management philosophy is the execution of risk-adjusted returns through prudent risk-taking that protects Morgan Stanley's capital base, liquidity and franchise. You will receive on-the-job training and benefit from working alongside experienced professionals on a variety of projects. This role crosses over multiple areas of Risk giving you exposure to teams not limited to Risk Analytics, Credit Risk, Market Risk, Stress Testing and Model Risk Management. Work closely with the Risk team to help to: develop and enhance risk management tools or advanced market risk and credit risk capital models perform model performance monitoring and model validation perform quantitative analysis on quarter-on-quarter changes of model outputs prepare departmental presentations, including e.g. presentations to Committees or regulators review and take meeting minutes compile risk data into spreadsheets and ensure completeness and accuracy of data in the tools and systems by performing reconciliations with the source

About the company

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, wealth management and investment management services. With offices in more than 41 countries, the Firm's employees serve clients worldwide including corporations, governments, institutions and individuals.

Skills

python
r
matlab
vba
data analysis