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Dec 18, 2023
Dec 18, 2023-September 2024
Budapest
Sep 20, 2024
ABOUT MORGAN STANLEY
Morgan Stanley mobilizes capital to help governments, corporations, institutions and individuals around the world achieve their financial goals.
10,000+ employees
Financial Services, Technology
VIEW COMPANY PROFILE >>
About Dec 18, 2023

  Are you interested in how mathematical models help the business? What could be the risk when we use these models in the financial industry? You will gain insight into global model risk management.

  We offer:

  • A competitive compensation and benefits package

  • Flexible working arrangements (core hours and opportunity to work from home)

  • Intellectual challenges that provide opportunity for constant learning and advancement

  • Professional development opportunities including access to Morgan Stanley's world-class internal trainings

  • A supportive and vibrant multinational environment, we accept individual differences and believe in teamwork

  • Contingent/Leased assignment working onsite at Morgan Stanley

  • Contract via 3rd party agency

  You will:

  • Review, test, challenge and build independent benchmarks for statistical models used in stress testing and risk management

  • Interact with a diverse group of global stakeholders from various areas of the Firm

  • Produce written model review reports

  • Conduct real-time analyses of model performance in response to market events

  • Participate in the model control and model risk management processes of the Firm

  QUALIFICATIONS

  You have:

  • At least a Bachelor's degree in Economics, Mathematical Finance, Mathematics, Physics, Engineering, Statistics or a related quantitative field (Master's or Ph.D. is an advantage)

  • Genuine and broad interest in financial markets, data and modelling; internal drive to spot, challenge and fix potential gaps and inconsistencies in statistical models using quantitative methods

  • Logical thinking, good business sense and judgment

  • Strong interpersonal and communication skills

  • Experience or strong interest in programming in a high-level language such as R or Python

  You might also have:

  • Familiarity with risk management and stress testing concepts

  • Familiarity with corporate finance

  Team Profile:

  The Lending & Enterprise Model Risk Management team is part of the Model Risk Management department of Morgan Stanley, and it has global responsibility for the independent risk control, review and validation of Enterprise models used by Morgan Stanley. These include lending credit risk models, operational risk models, liquidity risk models, revenue forecast models, etc. Model Risk Management professionals are located in New York, London, Mumbai and Budapest, and they work closely with business quantitative strategists, risk managers and financial controllers. The Budapest Lending & Enterprise team works closely with other members of the global team and covers majority of model classes in this space.

  About us:

  Morgan Stanley provides a superior foundation for building a professional career - a place for people to learn, achieve and grow. You will be exposed to a truly international and multi-cultural environment that appreciates and respects individuality. Our state-of-the-art offices in the City Centre have been designed to maximize collaboration.

  Interested in flexible working opportunities? Morgan Stanley empowers employees to have greater freedom of choice through flexible working arrangements. Speak to our recruitment team to find out more.

  Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximise their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing and advancing individuals based on their skills and talents.

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