Log In
Sign Up
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 MLOps 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 3-5.5 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).
Registration Required
> None
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.
