Data Scientist (Hybrid) at Morgan Stanley

Montreal, Quebec, Canada -

Full Time

Start Date

Immediate

Expiry Date

24 Feb, 26

Salary

0.0

Posted On

26 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analytics, Graph-Based Techniques, Statistical Analysis, Quantitative Models, Graph Databases, Network Analysis Tools, PySpark, Hadoop, Cloud Computing, Financial Crime Typologies, BSA/AML Regulations, Communication Skills, Collaboration, Research and Development, Problem Solving

Industry

Financial Services

Description

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. Advanced quantitative degree in machine learning, statistics, mathematics, data science, computer science, engineering, or other highly quantitative fields. 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. Experience with graph databases and network analysis tools (e.g. NetworkX, Neo4J) Experience using PySpark in distributed environments like Hadoop and cloud In-depth knowledge of financial crime typologies, BSA/AML regulations and experience with financial crime specific platforms (e.g. Actimize, Quantexa) Strong presentation, written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical audiences. 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. 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. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential.

Responsibilities

Develop and implement advanced data analytics solutions for financial crimes detection and prevention. Collaborate closely with stakeholders to deliver analytics solutions from conception to deployment.