Jobs
Risk Analytics IMM Counterparty Credit Risk, Analyst/ Associate, Firm Risk Management

Risk Analytics IMM Counterparty Credit Risk, Analyst/ Associate, Firm Risk Management
Mumbai, Maharashtra, India
·
On-site
·
Full-time
·
1mo ago
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Healthcare
•401k
•Equity
Required Skills
Quantitative Modeling
Risk Management
Python
SQL
C
VBA
R
Matlab
Mathematical Analysis
Statistics
Communication
We’re seeking someone to join our team as an Analyst in Risk Analysis IMM Counterparty Credit Risk 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:
Primary Responsibilities include, but are not limited to:
- Research, development, enhancement, and documentation of IMM Counterparty credit risk, methodologies, and tools for regulatory and risk management purposes
- Perform analysis including model recalibrations, back-tests, stress tests, scenario, and sensitivity analyses.
- Programming of prototypes/production code (within an established C/R /Python libraries) which will be productionized.
- Program, test and implement quantitative financial methods using Python, C, VBA, R, Matlab and SQL
- Utilize advanced statistics, econometrics and mathematical skills including probability theory, stochastic calculus, Monte Carlo simulation, numerical analysis, optimization techniques and time series analysis
- Work with Technology on model testing, implementation, and production
- Collaborate with risk managers and other stakeholders to address their requests and for relevant model enhancements
- Participate in Regulatory and validation exams by providing documentation and responses to regulators and internal validators
What you’ll bring to the role: Skills Required
- 0-2 (Analyst), 2.5 (Associate) years of work experience in quantitative modeling, Risk Management, algorithmic trading
- Analytical skills and ability to work with diverse cultures in a global team.
- Strong knowledge of financial traded products e.g. derivatives and their pricing.
- Knowledge and hands-on experience in one of the programming languages R, Python, MATLAB, C# or C is strongly preferred.
- Excellent communication skills (Oral and written). Ability to communicate and present logically, precisely and in simple manner, complex and technical issues.
Required Qualifications
- Graduate/Under-graduate/Advance degrees in finance, mathematics, physics econometrics, engineering or other quantitative subjects.
- Candidates should have a strong theoretical foundation in mathematics, quantitative finance and derivatives.
- Candidates will have to deal in Python, SQL queries, and MS-Office on daily basis.
Desirable Skillsets
- FRM, CFA, CQF certification is an advantage.
- Quantitative modeling experience in Finance/ Data Science
- Knowledge of risk mitigation practices and experience with Basel II/III/IV rules will be considered advantageous.
- Experience in one of the following AI, ML, NLP, Big Data Analytics, Tableau is an advantage
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 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
PublicA 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
Director
Junior/L3 · Operations Analyst
441 reports
$83,240
total / year
Base
$76,802
Stock
-
Bonus
$6,438
$60,778
$115,186
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
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