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职位Morgan Stanley

Portfolio Analytics Quants , ISG Operations, Senior Associate , Fund Services

Morgan Stanley

Portfolio Analytics Quants , ISG Operations, Senior Associate , Fund Services

Morgan Stanley

Mumbai, Maharashtra, India

·

On-site

·

Full-time

·

3w ago

必备技能

Python

Senior Associate, Portfolio Analytics – Quantitative Analytics, Fund Services

We are seeking a Senior Associate to join our Portfolio Analytics team, supporting performance, exposure, and risk attribution analysis for hedge fund portfolios using multi‑factor models. The role also contributes to the development and testing of systematic quantitative solutions across the firm’s hedge fund platform.

Established in 2004, Morgan Stanley Fund Services (MSFS)is a global business within the Institutional Equities Division(IED), providing fund administration services for over$700 billion in assets across350+ hedge funds, private equity, and large family office clients. Our best‑in‑class offering spans accounting and investor services, portfolio analytics, middle‑office functions, regulatory and financial reporting, and tax services.

MSFS operates with a global team of 1,400+ professionals across New York, London, Glasgow, Dublin, Mumbai, Bengaluru, and Hong Kong. Joining MSFS offers a dynamic, collaborative environment with opportunities for continuous learning, innovation, and meaningful impact for our clients and the broader Morgan Stanley franchise.

About the Portfolio Analytics Team

The MSFS Portfolio Analytics team is a globally connected, client‑servicing group delivering advanced risk and performance insights to hedge fund clients. The team partners closely with clients and internal stakeholders to produce high‑quality analytics and bespoke reporting.

This differentiated MSFS service focuses on customized analytics to meet complex client requirements. Team members actively contribute to the development of new analytical capabilities through ad‑hoc scripting, automation initiatives, and collaboration with technology partners. We value problem‑solving, intellectual curiosity, and continuous improvement.

What You’ll Do

  • Deliver periodic and bespoke quantitative analysis related to portfolio exposure, risk, and performance
  • Support client engagement by partnering with global coverage teams to address client queries on factor and attribution analysis
  • Produce customized client reports involving risk and performance calculations
  • Contribute to automation and scalability of bespoke analytics using R, VBA, Python, or technology‑enabled solutions
  • Participate in ideation and development of new quantitative products, including systematic processes supporting pre‑trade analytics and content generation

What You’ll Bring

  • Master’s degree in a quantitative discipline such as Financial Engineering, Mathematics, Statistics, or Computing, with 2–4 years of relevant experience
  • Professional certifications (CFA, CQF, FRM) are an advantage
  • Strong understanding of equities and equity derivatives, with familiarity in multi‑factor risk models
  • Hands‑on programming experience in R or Python; familiarity with La TeX, Markdown, and Shiny is preferred
  • Strong analytical and problem‑solving skills with a quantitative mindset
  • Effective verbal and written communication skills, strong attention to detail, and the ability to work collaboratively in a global team 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.

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关于Morgan Stanley

Morgan Stanley

Morgan Stanley is an American multinational investment bank and financial services company headquartered at 1585 Broadway in Midtown Manhattan, New York City.

10,001+

员工数

New York

总部位置

$150B

企业估值

评价

3.2

10条评价

工作生活平衡

2.5

薪酬

2.8

企业文化

3.8

职业发展

3.2

管理层

3.5

45%

推荐给朋友

优点

Nice and welcoming people/coworkers

Good career foundation and growth opportunities

Great management and benefits

缺点

Limited conversion to full-time positions

Poor compensation for junior employees

High turnover and branch politics

薪资范围

6,255个数据点

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

49份报告

$109,250

年薪总额

基本工资

$95,000

股票

-

奖金

-

$73,554

$143,750

面试经验

5次面试

难度

3.2

/ 5

时长

21-35周

体验

正面 0%

中性 80%

负面 20%

面试流程

1

Application Review

2

HR Screen/HireVue

3

Technical Interview

4

Superday/Final Round

5

Offer Decision

常见问题

Technical Knowledge

Behavioral/STAR

Finance/Investment Concepts

Case Study

Culture Fit