Model Risk Management (Traded Risk) - Senior Associate
Job Details
Full Job Description
What we’re looking for:
· Masters
or Ph.D. degree (or equivalent) in Finance, Economics, Mathematics,
Physics, Engineering, or a related quantitative field
· In-depth knowledge of mathematical finance,
derivative pricing, and numerical techniques
·
The ideal candidate has strong experience with market risk models
gained at a financial institution
·
Experience developing pricing and risk models using Python, R or Excel
VBA is a plus
· 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. 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.
Model Risk Management
(Traded Risk) – Senior Associate
London
3244094
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.
This
role resides within FRM's Model Risk Management (MRM) Department which
is dedicated to providing independent model risk control, review and
validation of models used by Morgan Stanley. These include models used
to monitor market risk (IMA) counterparty credit risk (CVA/IMM),
credit risk (IRB), operational risk, capital and liquidity stress
tests as well as valuation models.
MRM professionals in New
York, London, Budapest, Frankfurt, Mumbai and Tokyo work closely with
business quantitative strategists, risk analytics, risk managers and
financial controllers. The London team works collaboratively with
members of Model Risk Management across all model areas globally.
About Morgan Stanley
Morgan Stanley is a leading global financial services
firm providing a wide range of investment banking, securities,
investment management and wealth management services.
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. We 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.
What will you be doing?
·
Conduct model validation for market risk models (VaR/Stressed
VaR/Risks not in VaR/FRTB) by challenging model assumptions,
mathematical formulation, and implementation
·
Conduct independent testing to assess model accuracy and robustness
under different scenarios and market conditions
· Assess and quantify model risks due to model limitations
and develop compensating controls
·
Develop high-quality validation reports highlighting risks and
limitations of models and communicate findings to stakeholders, senior
management, and governance committees
·
Collaborate with Global MRM teams, Model Control Officers, Valuation
Control and Risk Managers to manage model risk across the model
lifecycle
· Assist in cultivating
and managing effective relationships with regulators by providing
accurate and timely submissions