Morgan Stanley's CYBER DATA RISK & RESILIENCE team, specifically the Fraud Operations division, needs to enhance its ability to detect and prevent internal and external fraud risk by leveraging data analytics and AI/ML techniques. The Fraud Analytics and Data Science Team (ADS) requires support in developing data-driven solutions to safeguard clients and the Firm.
Requirements
- Experience using relational databases (e.g. SQL, Hive, Impala, Hadoop) for business reporting and metrics development
- Experience using Python (or similar languages) to conduct analytic inquires
- Knowledge of, and experience working with data related to cryptocurrency or blockchain domains
- Experience in developing an understanding of large data sets coupled with an ability to use that data to answer questions posed by business owners
- Analytical, critical thinking and decision-making skills utilizing data extraction
- Experience or knowledge in financial services and/or fraud
- Experience in cryptocurrency-based fraud investigations
Responsibilities
- Analyze large datasets to identify trends, detect anomalies, and support fraud department reporting requests.
- Develop clear, actionable data outputs for business leaders and stakeholders.
- Collaborate with teams across fraud department, technology, risk and compliance to enhance data-driven decision-making.
- Ensure data integrity, accuracy, and compliance with established firm and department standards.
- Communicate complex data insights in a simple, compelling way to both technical and non-technical audience.
- crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility
- applying machine learning and AI-based techniques
Other
- Ability to verbally and in writing summarize and/or describe business processes and requirements
- Excellent written and verbal communication skills
- Detail oriented with the ability and desire to work in a team environment
- Understanding of fraud and security issues within the banking and finance industry
- Experience with data analytics in the context of fraud investigation, Financial Services, payment processing, and/or similar fields
