Machine Learning, Associate, WM Admin, Wealth Management

Morgan Stanley; Mumbai; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Morgan Stanley in Mumbai seeks an experienced analytics professional to build ML models for Wealth Management, working hands-on with data to generate predictive insights and business intelligence for global teams.

You will experiment with modeling approaches, assist with deployment and monitoring, and collaborate with Risk, Legal, and Compliance to ensure compliant solutions. A quantitative degree and 3–5 years of ML experience are expected.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a quantitative field.
• 3–5 years of experience in Machine Learning, preferably in financial services.

Responsibilities

• Support development of ML solutions for Wealth Management use cases with guidance from senior team members.
• Experiment with different modeling approaches to improve performance and learning.
• Collaborate with model risk, validation, and control partners to document and test model behavior.
• Deploy and monitor models in production with ML Ops and engineering teams, including troubleshooting.

Skills

ML algorithms

Python

Git

MLflow

OOP

Data structures

Communication

Cloud/PaaS

PyTorch

TensorFlow

Education

Bachelor's or Master's in CS/Math

Tools

Git

MLflow

PyTorch

TensorFlow

Job description

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:

• 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.