Job Description

We're seeking someone to join our team as an Associate to join our Global Supplier Services Data & Analytics Innovation Team. This role combines expertise in Power BI dashboard development, Snowflake data engineering, and Data Science/AI modeling to deliver advanced analytics solutions that drive strategic decision-making across global initiatives.




In the Corporate Services division, we empower our businesses by creating collaborative workplace solutions and commercial services that enhance the employee and client experience, while optimizing the value of our sourcing and third-party lifecycle to enable the Firm to do-and-win business. This is an Associate level position within the within Sourcing / Procurement, which is responsible for procurement (e.g., purchasing and supply chain activities), as well as vendor management (e.g., business requirements gathering, sourcing strategy, competitive and market assessments, negotiation, contracting, and relationships associated with outsourced services).


Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.


Interested in joining a team that's eager to create, innovate and make an impact on the world? Read on...

What you'll do in the role:

Dashboard Development (Power BI): Design, build, and maintain advanced Power BI dashboards for sourcing analytics, GSS reporting, and executive insights. Translate business requirements into intuitive, interactive visualizations and optimize performance using best practices in DAX, Power Query, and data modeling. Data Engineering & Architecture (Snowflake): Develop and optimize Snowflake SQL queries, views, and stored procedures to support large-scale analytics and reporting needs. Design and operationalize cross-system data flows and distributed applications for analytics and AI/ML initiatives. Predictive Modeling & AI/ML: Build and deploy predictive models for sourcing forecasts, supplier risk scoring, and spend optimization using Python and ML frameworks (e.g., scikit-learn, TensorFlow, Snowflake Cortex). Enable AI-driven data enrichment and GenAI capabilities to enhance user experience and decision-making. Automation & Cloud Enablement: Contribute to automation of recurring workflows and support migration to cloud-native ETL platforms for improved scalability and efficiency. Collaboration & Stakeholder Engagement: Partner with global business stakeholders to gather requirements, refine objectives, and deliver actionable insights. Participate in GSS strategy change projects, bringing data-driven insights and visualization capabilities to transformation efforts. Innovation & Continuous Improvement: Identify opportunities to streamline processes, enhance analytics capabilities, and explore new data sources and domains. Contribute to metadata management, data modeling, and documentation to ensure robust governance and transparency.

What you'll bring to the role:

At least 4 years of experience in data analytics, dashboard development, and predictive modeling in a professional setting with a Bachelor's or Master's degree in computer science, Data Analytics, Information Systems, or a related field. Proven ability to analyze and synthesize large datasets from diverse sources, including SQL and Snowflake. Strong proficiency in Power BI, with hands-on experience building scalable, interactive dashboards and applying best practices in DAX and data modeling.

Solid working knowledge of Python for automation, data processing, and enabling AI/ML workflows.
Familiarity with AI/ML concepts and frameworks (e.g., scikit-learn, TensorFlow, Snowflake Cortex) for predictive analytics and intelligent reporting.

Experience with ETL platforms and data integration tools (e.g., Dataiku, Lightning, Alteryx) is a plus.
Understanding of cloud-based data architecture, distributed systems, and data governance principles.
At Morgan Stanley Montreal, we support the Firm's global businesses and infrastructure with cutting edge technology and innovation. The multi-faceted and highly technical Montreal team plays a critical role in building and maintaining our leading technology platform, including electronic trading, algorithm trading, data analytics, cloud engineering, cybersecurity and digital technologies. Morgan Stanley has been rooted in the Montreal community since 2008 and is considered a leading employer among the area's highly skilled technology talent.


All our positions are located in Montreal, Quebec. We offer a hybrid work environment, combining remote work and attendance in the office.


Knowledge of French and English is required.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 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.