Company Profile

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm’s employees serve clients worldwide including corporations, governments, and individuals from more than 1,200 offices in 43 countries.

As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.

Firm Risk Management

Firm Risk Management (FRM) supports Morgan Stanley to achieve its business goals by partnering with business units across the Firm to realize efficient risk-adjusted returns, acting as a strategic advisor to the Board and protecting the Firm from exposure to losses as a result of credit, market, liquidity, operational, model and other risks.

The role will reside within Firm Risk Management’s Risk Analytics Department, specifically the Credit Risk Methodology Group. This team is responsible for development of credit risk models for estimation of ratings, and probability of default, primarily for use in Internal Ratings Based (IRB) capital calculations but also other downstream processes.

This role will be within the EMEA Credit Risk Methodology team, based in London, working closely within the global function in the US and other locations. The EMEA team, in addition to contributing to global workstreams and priorities, focuses on ensuring that specific regional / legal-entity requirements, standards and practices are met.

What you’ll do in the role:
• Enhance existing Corporate Subsidiaries models, and legal entity specific PD Calibration models, while ensuring compliance with different regulatory requirements (UK, EU) and internal standards
• Collaborate in a global team environment to execute projects such as model enhancement of above models benchmarking, testing and performance monitoring of above models
• Support line-by-line self-assessment processes against relevant regulations such as CRR, EGIM for above models
• Review and challenge the data and assessments provided by Credit, seek second line approval by demonstrating model conceptual soundness, and strong model performance, as well as ensure compliance with relevant global and regulatory standards for the above models
• FRM is committed to creating and providing opportunities that enable our workforce to reflect diverse backgrounds and views.

What you’ll bring to the role:
• MSc or equivalent in a quantitative subject
• Understanding rapidly evolving landscape of statistical techniques used in risk modelling such as machine learning.
• Strong analytical ability and programming skills (Python [preferred], R)
• Knowledge of relevant IRB model class
• Knowledge of relevant IRB regulations and requirements (UK and EU)
• Collaborate with teams and stakeholders throughout FRM
• The ability to effectively communicate with a wide range of stakeholders, both written and verbally
• An interest in working in a fast-paced environment, often balancing multiple high priority deliverables

Flexible work statement:

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.

Equal opportunities statement:

Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize 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.

What you’ll do in the role:
• Enhance existing Corporate Subsidiaries models, and legal entity specific PD Calibration models, while ensuring compliance with different regulatory requirements (UK, EU) and internal standards
• Collaborate in a global team environment to execute projects such as model enhancement of above models benchmarking, testing and performance monitoring of above models
• Support line-by-line self-assessment processes against relevant regulations such as CRR, EGIM for above models
• Review and challenge the data and assessments provided by Credit, seek second line approval by demonstrating model conceptual soundness, and strong model performance, as well as ensure compliance with relevant global and regulatory standards for the above models
• FRM is committed to creating and providing opportunities that enable our workforce to reflect diverse backgrounds and views.

What you’ll bring to the role:
• MSc or equivalent in a quantitative subject
• Understanding rapidly evolving landscape of statistical techniques used in risk modelling such as machine learning.
• Strong analytical ability and programming skills (Python [preferred], R)
• Knowledge of relevant IRB model class
• Knowledge of relevant IRB regulations and requirements (UK and EU)
• Collaborate with teams and stakeholders throughout FRM
• The ability to effectively communicate with a wide range of stakeholders, both written and verbally
• An interest in working in a fast-paced environment, often balancing multiple high priority deliverables

Flexible work statement:

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.

Equal opportunities statement:

Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize 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.