Job Description

Director - Quant ML/Fraud Models - Model Risk (Firm Risk Management)

Job Number:

3254789


POSTING DATE: Jun 30, 2024
PRIMARY LOCATION: Non-Japan Asia-India-India-Mumbai (MSA)
EDUCATION LEVEL: Bachelor's Degree
JOB: Model Risk
EMPLOYMENT TYPE: Full Time
JOB LEVEL: Associate

DESCRIPTION

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.


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, model and other risks.



Primary Responsibilities
The primary responsibilities of the role include, but are not limited to the following:

• Provide independent review and validation compliant with MRM policies and procedures, regulatory guidance and industry leading practices, including evaluating conceptual soundness, quality of model / tool methodology, model / tool limitations, data quality, and on-going monitoring of model / tool performance
• Take initiatives and responsibility of end-to-end delivery of a stream of Model and Tool Validation and related Risk Management deliverables
• Write Model and Tool Review findings in validation documents that could be used for presentations both internally (model and tool developers, business unit managers, Audit, various global Committees) as well as externally (Regulators)
• Verbally communicate results and debate issues, challenges and methodologies with internal audiences including senior management
• Represent MRM team in interactions with regulatory and audit agencies as and when required
• Follow financial markets & business trends on a frequent basis to enhance the quality of Model and Tool Validation and related Risk Management deliverables.



QUALIFICATIONS


Qualifications Skills required (essential / preferred)

• Masters or Doctorate degree in a quantitative discipline such as Statistics, Mathematics, Physics, Computer Science or Engineering is essential
• Experience in a Quant role in validation of Models / Tools, in developments of Models / Tools or in a technical role in Financial institutions e.g. Developer, is essential
• Strong written & verbal communication skills including debating different viewpoints and making formal presentations of complex topics to a wider audience is preferred
• 5+ years of relevant work experience in a Model / Tool Validation role in a bank or financial institution
• Proficient programmer in Python ; knowledge of other programming languages like R, Scala, MATLAB etc. is preferred
• Willingness to learn new and complex topics and adapt oneself (continuous learning) is preferred
• Working knowledge of statistical techniques, quantitative finance and programming is essential; good understanding of various complex financial instruments is preferred
• Knowledge of popular machine learning techniques is preferred
• Relevant professional certifications like CQF, CFA or progress made towards it are preferred
• Desire to work in a dynamic, team-oriented, fast-paced environment focusing on challenging tasks mixing fundamental, quantitative, and market-oriented knowledge and skills is essential


"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".