Morgan Stanley is looking to prevent financial crimes, including money laundering, market manipulation, insider trading, and other financial crimes, by developing and implementing advanced data analytics solutions.
Requirements
- Master's degree in machine learning, statistics, mathematics, data science, computer science, engineering, or other highly quantitative fields.
- 7 years of hands-on industry experience in building quantitative models including supervised and unsupervised machine learning and applied statistical analysis with at least 5 years focused on financial crime prevention.
- In-depth knowledge of software design principles and excellent skills in one or more programming languages including Python, R, Java, Scala.
- In-depth knowledge of financial crime typologies, BSA/AML regulations, OFAC sanctions, investigative methodologies or fraud analytics.
- Experience with financial crime specific platforms {e.g. Actimize, Quantexa)
- Experience with graph databases and network analysis (e.g. NetworkX, Neo4J).
- Experience with deep learning frameworks including PyTorch or TensorFlow.
Responsibilities
- Lead the development and implementation of advanced data analytics solutions for financial crimes prevention, including transaction monitoring, suspicious activity reporting, sanction screening, and customer risk ranking.
- Collaborate closely with stakeholders in the Financial Crimes, Compliance, Legal, and IT departments to deliver analytics solutions from conception to deployment.
- Guide financial investigations leveraging graph-based approaches, graph analytics infrastructure, and data sourcing efforts to identify client behavior patterns.
- Conduct research efforts to identify novel methods to deliver efficiency and effectiveness across analytical solutions.
- Manage and provide guidance to junior data scientists and analysts in the team.
- Ensure compliance with BSA/AML regulations and standards in all data analytics activities.
Other
- Master's degree in a relevant field.
- Strong presentation and communication skills, with the ability to articulate complex technical concepts to non-technical audiences.
- Commitment to diversity and inclusion.
- Ability to work in a team environment.
- Adherence to Morgan Stanley's policies and standards of integrity and excellence.
