Jobs
Benefits & Perks
•Learning and development stipend
•Annual team offsites
•Wellness benefits
•Top Tier compensation with equity
•Flexible PTO policy
•Remote work flexibility
Required Skills
Python
Airflow
SQL
We're seeking someone to join our team as an Associate in the Non-Financial Risk (NFR) department to support the Financial Crime team to maintain, develop, design and optimize surveillance models, approaches, and tools using advanced analytical techniques like supervised and unsupervised machine learning, and evolving techniques like graph analytics. These surveillances and other tools help identify suspicious and/or illegal behaviors such as money laundering, market manipulation, insider trading, unfair sales or trading practices, and other financial crimes
In the Legal & Compliance division, we assist the Firm in achieving its business objectives by facilitating and overseeing the Firm's management of legal, regulatory and franchise risk. This is an Associate level position within the Data and Analytics department to support the team as they develop and maintain tooling for the wider Privacy NFR team.
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:
- Develop and implement advanced data analytics solutions for financial crimes detection and prevention.
- Use graph-based techniques, graph analytics infrastructure to identify client behavior patterns to assist in financial crime investigations and build solutions for financial crime detection.
- Perform statistical and quantitative analysis to support inclusion of risk attributes, analyze, and propose thresholds for financial crime detection controls.
- Conduct research and development efforts to identify novel methods to deliver efficiency and effectiveness across analytical solutions.
- Collaborate closely with stakeholders in the Global Financial Crimes, Technology and Model Risk Management departments to deliver analytics solutions from conception to deployment.
What you'll bring to the role:
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Advanced quantitative degree in machine learning, statistics, mathematics, data science, computer science, engineering, or other highly quantitative fields.
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3+ years of hands-on industry experience in conducting statistical analysis, developing quantitative models and deploying production quality code adhering to best practices and SDLC standards.
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Experience with graph databases and network analysis tools (e.g. NetworkX, Neo4J)
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Experience using Py Spark in distributed environments like Hadoop and cloud
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In-depth knowledge of financial crime typologies, BSA/AML regulations and experience with financial crime specific platforms (e.g. Actimize, Quantexa)
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Strong presentation, written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical audiences.
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.
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About Morgan Stanley

Morgan Stanley
PublicA financial services company that offers securities, asset management, and credit services.
10,001+
Employees
New York
Headquarters
Reviews
3.5
4 reviews
Work Life Balance
3.0
Compensation
2.5
Culture
3.2
Career
3.0
Management
3.0
35%
Recommend to a Friend
Pros
Skills evaluation through business plans and projects
Direct access to senior leadership interviews
Conversational interview format
Cons
Automated resume screening system issues
Focus on formatting over qualifications
Compensation concerns and salary expectations
Salary Ranges
11,766 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
1,682 reports
$114,371
total / year
Base
$96,366
Stock
-
Bonus
$18,005
$77,808
$170,800
Interview Experience
6 interviews
Difficulty
3.0
/ 5
Duration
21-35 weeks
Experience
Positive 16%
Neutral 84%
Negative 0%
Interview Process
1
Initial screening (HR/HireVue)
2
Technical rounds
3
Manager/Senior leadership interviews
4
Final round/Superday
Common Questions
Technical knowledge assessment
Behavioral questions
Role-specific scenarios
Leadership and teamwork examples
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