Risk Analytics Internal Models Method, Director, Firm Risk Management
Morgan Stanley · Mumbai, Maharashtra, India
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- On site
- Full-time
- $200,000 / year
- Mumbai, Maharashtra, India
Job highlights
- Develop and implement risk calculation models.
- Analyze model performance and recalibrations.
- Program prototypes in Python for production.
- Collaborate with risk and technology teams.
- Requires advanced quantitative and programming skills.
About the role
Director, Risk Analytics Internal Models Method
We’re seeking someone to join our team as an Director in Risk Analytics team. In the Firm Risk Management division, we advise businesses across the Firm on risk mitigation strategies, develop tools to analyse 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
- Build, transform and implement models for exposure calculations along all asset classes. This includes research, development, enhancement, and documentation of IMM Counterparty credit risk methodologies and tools for regulatory and risk management purposes.
- Develop and implement ongoing monitoring and tracking methods for different key metrics.
- Perform analysis including model recalibrations, back-tests, stress tests, scenario, and sensitivity analyses.
- Programming of prototypes (within an established Python library) which will be productionized.
- Support the risk management teams with information and analysis, executing investigation on unexpected or irregular behavior of market simulation or pricing models.
- Work with Technology on model testing, implementation, and production.
- Produce ad hoc deliverables and reporting materials.
What You’ll Bring To The Role
- MSc. or PhD in mathematical finance, mathematics, physics, statistics, engineering, computer science, informatics or similar quantitative area.
- Solid mathematical foundations, especially probability theory and statistics.
- Strong analytical and problem-solving skills.
- Advanced statistics, econometrics and mathematics skills including probability theory, stochastic calculus, monte carlo simulation, optimization techniques.
- Strong knowledge of financial traded products e.g. derivatives and their pricing.
- Knowledge and hands-on experience in one of the programming languages Python, MATLAB, C# or C++.
- Self-motivated personality with high standards for quality of work and accuracy, and attention to details.
- Excellent communication skills (Oral and written). Ability to communicate and present logically, precisely and in simple manner, complex and technical issues.
- Ability and willingness to work with virtual teams across the regions contributing to common goals.
- Aptitude to work in a fast-paced, high energy level environment.
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.
Key skills/competency
- Risk Analytics
- Internal Models Method
- Director
- Morgan Stanley
- Firm Risk Management
- Quantitative Analysis
- Model Development
- Python
- Financial Products
- Regulatory Initiatives
Skills & topics
- Risk Analytics
- Internal Models Method
- Director
- Morgan Stanley
- Firm Risk Management
- Quantitative Analysis
- Model Development
- Python
- Financial Products
- Regulatory Initiatives
- MSc
- PhD
- Probability Theory
- Statistics
- Stochastic Calculus
- Monte Carlo Simulation
- Optimization
- Derivatives Pricing
- MATLAB
- C#
- C++
- Risk Mitigation
- Data Analysis
- Financial Services
How to get hired
- Tailor your resume: Highlight your quantitative background, modeling experience, and programming skills relevant to risk analytics and internal models.
- Showcase financial product knowledge: Emphasize your understanding of derivatives and their pricing, as well as your experience with Python, MATLAB, C#, or C++.
- Demonstrate problem-solving: Prepare to discuss complex analytical challenges you've overcome and how you approached them.
- Highlight communication skills: Be ready to explain technical concepts clearly and concisely, both verbally and in writing.
- Research Morgan Stanley: Understand their values, global presence, and commitment to risk management to align your application.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key quantitative qualifications for the Director, Risk Analytics Internal Models Method role at Morgan Stanley?
- The Director, Risk Analytics Internal Models Method position at Morgan Stanley requires an MSc or PhD in a quantitative field such as mathematical finance, mathematics, physics, statistics, engineering, computer science, or informatics. A strong foundation in probability theory, statistics, stochastic calculus, and optimization techniques is essential. Experience with advanced statistics and econometrics is also highly valued.
- What programming languages are preferred for the Director, Risk Analytics Internal Models Method position at Morgan Stanley?
- For the Director, Risk Analytics Internal Models Method role at Morgan Stanley, proficiency in Python is a key requirement, particularly for programming prototypes. Experience with other languages like MATLAB, C#, or C++ is also beneficial and considered valuable hands-on experience.
- How does Morgan Stanley support diversity and inclusion in its hiring for Risk Analytics roles?
- Morgan Stanley is committed to fostering a supportive and inclusive environment. They actively recruit and develop individuals based on skills and talents, drawing from a broad cross-section of global communities to ensure a diverse workforce with varied backgrounds, talents, perspectives, and experiences.
- What kind of analysis is expected from the Director, Risk Analytics Internal Models Method at Morgan Stanley?
- The Director, Risk Analytics Internal Models Method will perform various analyses, including model recalibrations, back-tests, stress tests, scenario analyses, and sensitivity analyses. This involves investigating model behavior and supporting risk management teams with critical insights.
- Can I apply for the Director, Risk Analytics Internal Models Method role at Morgan Stanley if I have experience with just one programming language?
- While Python is a key programming requirement for this role, Morgan Stanley values hands-on experience in one of the listed languages (Python, MATLAB, C#, or C++). Demonstrating strong programming skills in any of these will be considered positively.