Product Manager Data, Analytics & AI Vice President

Product Manager – Data, Analytics & AI – Vice President

Wealth Management Platforms
Calgary

In this role you will lead the development of a next-generation data and AI platform. This platform consolidates complex data across equity compensation and financial systems into an intelligent analytics layer. You will help shape how organizations unlock insights and intelligence from massive data sets, translating strategy into action and guiding a small product team, including a junior Product Manager and cross-functional partners in engineering, data, and design.
 

About Morgan Stanley

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm’s employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices in 43 countries.

Morgan Stanley is committed to helping its employees build meaningful careers and we strive to be a place for people to learn, achieve and grow.

Department Overview

In the Wealth Management division, we help people, businesses and institutions build, preserve, and manage wealth so they can pursue their financial goals

Wealth Management (WM) Platforms manages industry-leading platforms, across all WM channels and client segments, to provide a unified digital experience, unlock growth, and deliver efficiencies for Advisors, Clients, and Institutions. WM Platforms consists of nine sub-teams including: Field Experience & Platforms, Digital Client Experience & Platforms, Workplace Platforms, Automation & Workflow Solutions, Digital Trading & Investing, UX Design & Research, Strategy & Execution. Business Control & Support, and the Chief Operating Office.

Workplace Platforms is a division within Morgan Stanley Wealth Management Platforms, comprised of the digital platforms supporting the Morgan Stanley at Work businesses—including Equity Compensation, Retirement Plan Solutions, and Deferred Compensation. The Workplace Platforms team drives and defines the digital and online experience for wealth management and corporate clients. The overall mission of the division is to create a best-in-class experience for both corporate clients and their employees (“participants”) as we engage them throughout their financial life journey, ultimately leading to a deepening of their Morgan Stanley Wealth Management relationship. Our approach will be highly scalable, leveraging an omni-channel strategy with an emphasis on messaging, onboarding, cross-selling, activation and servicing.  Our goal will be to drive growth across all client segments, with new digital capabilities. 

What you’ll do in the role:

• Translate long-term vision and product roadmap for analytics & AI.
• Translate business and technology opportunities into actionable requirements and prioritized backlogs.
• Define success metrics and establish measurable impact goals.
• Collaborate closely with data engineering and analytics teams to shape data architecture, metrics strategy, data pipelines and AI/ML use-cases.
• Lead end-to-end product development from concept through launch, ensuring every release delivers measurable high-impact outcomes.
• Partner with the other Product Manager; help craft requirement documents, review use stories, guide roadmap updates, and facilitate stakeholder communication.
• Engage senior leadership and stakeholders with compelling storytelling, data-backed business cases and clear linkages to strategic outcomes.
• Shape the data pipeline strategy, ensuring governance, quality, and compliance.
• Support development in dashboard metric frameworks and data sharing APIs for analytics and insights generation.

Skills Required:

• 7+ years of product management experience, ideally in analytics, data platforms, AI/ML or enterprise SasS.
• Strong background in working with large-scale data systems (data warehouse, analytics tools, dashboards), metrics/insights-driven product development.
• Experience defining long-term product vision for data and analytics platforms.
• Working knowledge of AI/ML concepts, large language models (LLMs) or intelligent automation workflows.
• Understanding of modern data stacks, APIs, ETLs, data warehouse schema design, and metric frameworks.
• Proven ability to deliver complex products in a matrixed, regulated enterprise environment.
• Excellent communication skills: able to translate technical product details into business value, present to senior leadership and influence stakeholders.
• Analytical mindset, curious, comfortable with ambiguity and able to prioritize effectively.

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.