Company Profile:
Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.
At Morgan Stanley India, we support the Firm's global businesses, with critical presence across Institutional Securities, Wealth Management and Investment management, as well as in the Firm's infrastructure functions of Technology, Operations, Finance, Risk Management, Legal and Corporate & Enterprise Services. Morgan Stanley has been rooted in India since 1993, with campuses in both Mumbai and Bengaluru. We empower our multi-faceted and talented teams to advance their careers and make a global impact on the business. For those who show passion and grit in their work, there's ample opportunity to move across the businesses.
Morgan Stanley is an equal opportunity 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.
Department Profile:
The Analytics & Data (A&D) organization is a key growth area within Morgan Stanley's Wealth Management Division, playing a critical role in the execution of the wider Wealth Management strategy. The team owns all the executive reporting, insights, and predictive modeling in support of Wealth Management business. The use of analytics and data will be a key driver in accelerating growth across client segments, enabling data-driven decision making and delivering the best client experience.
Position Summary:
We are looking for an experienced professional to join the Analytics & Data organization who will be responsible for building ML models for WM business verticals. The candidate will work with data in a hands-on capacity to build models and generate predictive analytics, insights, and business intelligence that will help decision making and strategy. They will be responsible for monitoring and recalibration of models and delivery of their outcomes to US-based team members and leadership. The ideal candidate will display ability to work with minimal direction, curiosity about data, and the ability to determine and build timely solutions.
Key Responsibilities:
Key responsibilities will include but will not be limited to the following:
- Support the development of machine learning solutions for Wealth Management use cases, with guidance from senior team members.
- Experiment with different modeling approaches (including newer techniques) to improve performance and learn best practices.
- Work with model risk and validation partners to help document, test, and confirm model behavior and controls.
- Support deployment and monitoring of models in production in partnership with ML Ops and engineering, including basic troubleshooting and performance checks.
- Assist with A/B tests or controlled experiments to measure impact and summarize results clearly.
- Collaborate with business and control partners (Risk, Legal, Compliance) to ensure solutions are usable and follow required standards.
- Create clear slides or performance readouts that communicate model results to business stakeholders. Experience:
- Bachelor's or Master's degree (preferred) in Computer Science, Engineering, Mathematics, Physics, or an equivalent quantitative field.
- Associate: A minimum of 3 years of experience in Machine Learning domain (overall 3-5 years), preferably in the financial services industry
Required Skills:
- Possess theoretical knowledge and applications of machine learning algorithms in classification, regression, recommender systems, clustering, deep learning
- Proficiency in at least one of the modern programming languages (Python, C++, or a related language).
- Experience with code versioning systems such as Github, Bitbucket, and experiment tracking systems like ML Flow.
- Proficiency with computer science fundamentals in object-oriented design, data structures, and algorithmic design.
- Track record of working independently and solving problems creatively, as well as the ability to debug/maintain complex codes, with a strong sense of accountability and an eye for innovation
- Excellent oral and written communication skills, including the ability to present complex information in a clear and concise manner to audiences of various backgrounds/seniority; 2+ years in a client-facing position preferred
- Ability to work in a collaborative, transparent style within the team and with cross-functional stakeholders across the organization
Preferred Skills:
- Experience with Cloud or Big Data technologies such as Azure, AWS, Google Cloud, Hadoop, or an equivalent
- Familiarity with Deep Learning frameworks (PyTorch, Tensorflow, Py - Geometric, or equivalent).
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 opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Physics, or equivalent quantitative field
- Minimum 3 years experience in Machine Learning domain (overall 3-5 years)
- Theoretical knowledge and application of ML algorithms: classification, regression, recommender systems, clustering, deep learning
- Proficiency in at least one modern programming language (Python, C++ or related)
- Experience with code versioning systems (GitHub, Bitbucket) and experiment tracking (MLflow)
- Proficiency with computer science fundamentals: object-oriented design, data structures, algorithmic design
- Ability to debug and maintain complex code, work independently, and solve problems creatively
- Excellent oral and written communication skills; ability to present complex information clearly
- 2+ years in a client-facing position
- Ability to work collaboratively with cross-functional stakeholders (Risk, Legal, Compliance, ML Ops, Engineering)
- Experience with Cloud or Big Data technologies (Azure, AWS, Google Cloud, Hadoop)
- Familiarity with deep learning frameworks (PyTorch, TensorFlow, PyTorch Geometric)
Morgan Stanley Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Morgan Stanley and has not been reviewed or approved by Morgan Stanley.
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Parental & Family Support — Family support is extensive, with paid parental leave for all parents, adoption and fertility assistance, backup childcare, and eldercare resources. Feedback suggests these programs meaningfully enhance the overall package and help with retention.
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Healthcare Strength — Health coverage spans medical, dental, vision, mental‑health access, care navigation, and expert second opinions. Convenient primary care access and condition‑specific support reinforce the depth of healthcare coverage.
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Equity Value & Accessibility — Equity compensation and stock ownership are positioned as core motivators that encourage commitment and retention. Feedback suggests education and support are provided to help participants manage equity and related financial benefits.
Morgan Stanley Insights
What We Do
Morgan Stanley mobilizes capital to help governments, corporations, institutions and individuals around the world achieve their financial goals. For over 85 years, the firm’s reputation for using innovative thinking to solve complex problems has been well earned and rarely matched. A consistent industry leader throughout decades of dramatic change in modern finance, Morgan Stanley will continue to break new ground in advising, serving and providing new opportunities for its clients. Morgan Stanley is committed to maintaining the first-class service and high standard of excellence that have always defined the firm. At its foundation are five core values — putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back — that guide its more than 60,000 employees in 1,200 offices across 41 countries.







