Data Scientist enhancing merchandising and inventory performance using machine learning techniques at Nordstrom. Collaborating with teams to develop data - driven solutions for better customer experiences.
About the role
- Data Scientist developing advanced data analytics solutions for financial crime detection at Morgan Stanley. Collaborating with cross-functional teams to implement analytics solutions in a hybrid work environment.
Responsibilities
- 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.
Requirements
- 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.
Benefits
- health insurance
- retirement plans
- paid time off
- flexible work arrangements
- professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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