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Credit Risk Data Control (Model Monitoring), Analyst/ Associate, Firm Risk Management

Morgan Stanley

Credit Risk Data Control (Model Monitoring), Analyst/ Associate, Firm Risk Management

Morgan Stanley

Mumbai, India

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Generous paid time off and holidays

Parental leave

Team events and activities

401(k) matching

Flexible work arrangements

Comprehensive health, dental, and vision insurance

Parental Leave

Flexible Hours

Healthcare

Required Skills

TypeScript

React

PostgreSQL

We're seeking someone to join our team as a Analyst/ Associate in the Credit Risk Data Control (Model Monitoring) team.
In the Firm Risk Management division, we advise businesses across the Firm on risk mitigation strategies, develop tools to analyze and monitor risks and lead key regulatory initiatives.
Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

What you'll do in the role:

  • Lead data quality enhancements for model inputs used in counterparty credit exposure calculations, including CE, PFE, and EAD metrics.
  • Maintain and monitor the MPoR (Margin Period of Risk) framework, ensuring alignment with regulatory standards and exposure methodologies.
  • Implement new controls on simulation model parameters such as volatilities, correlations, and risk factors, supporting Monte Carlo and scenario-based exposure modelling
  • Evaluate proposals aimed at optimizing regulatory capital requirements.
  • Provide ad hoc portfolio analysis and risk insights to credit professionals and senior management, especially during periods of market volatility or regulatory review.
  • Collaborate with Credit Risk Analytics and IT teams to validate model implementations, conduct impact testing, and ensure consistency across simulation paths and pricing models.
  • Escalate data integrity issues to the Data Control team and Agile IT squads and support remediation efforts through structured diagnostics and stakeholder coordination.

What you'll bring to the role: :

  • Bachelor's degree in Finance, Computer Science, Engineering, or a related quantitative discipline.
  • Hands-on experience in counterparty credit risk exposure calculations under both IMM and standardized approaches.
  • Strong product knowledge across OTC derivatives and SFTs, with familiarity in MPoR, WWR (Wrong Way Risk), and collateral margining frameworks.
  • Advanced proficiency in Python for data analysis, automation, and model validation. Demonstrated ability to manage GitHub repositories for version control, collaborative development, and code reviews.
  • Skilled in SQL and Microsoft Office for data extraction, reporting, and portfolio diagnostics.
  • Proven ability to analyze large datasets, identify exposure trends, and communicate findings effectively.
  • Detail-oriented with strong organizational skills and the ability to manage multiple priorities in a fast-paced environment.
  • Excellent verbal and written communication skills, with a collaborative mindset for cross-functional engagement across geographies.
  • At least 3 years of relevant experience.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.
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.

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About Morgan Stanley

Morgan Stanley

A financial services company that offers securities, asset management, and credit services.

10,001+

Employees

New York

Headquarters

Reviews

3.5

4 reviews

Work Life Balance

3.0

Compensation

2.5

Culture

3.2

Career

3.0

Management

3.0

35%

Recommend to a Friend

Pros

Skills evaluation through business plans and projects

Direct access to senior leadership interviews

Conversational interview format

Cons

Automated resume screening system issues

Focus on formatting over qualifications

Compensation concerns and salary expectations

Salary Ranges

11,766 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

1,682 reports

$114,371

total / year

Base

$96,366

Stock

-

Bonus

$18,005

$77,808

$170,800

Interview Experience

6 interviews

Difficulty

3.0

/ 5

Duration

21-35 weeks

Experience

Positive 16%

Neutral 84%

Negative 0%

Interview Process

1

Initial screening (HR/HireVue)

2

Technical rounds

3

Manager/Senior leadership interviews

4

Final round/Superday

Common Questions

Technical knowledge assessment

Behavioral questions

Role-specific scenarios

Leadership and teamwork examples