Morgan Stanley is seeking a Director, Data and Analytics Engineer in Jersey City, NJ, to focus on identifying fraud trends and investigating suspicious behavior. The role involves analyzing various data sets to detect out-of-pattern transactions and combining internal data with external intelligence to enhance fraud detection. The successful candidate will work closely with the Data Science team to develop fraud risk models and communicate findings to management. This position allows for telecommuting up to two days per week.

• Requires a Bachelor’s in Economics, Data Science, Business Analytics or a related field.
• Requires three (3) years of experience in the position offered or three (3) years as an Associate, Senior Consultant, or a related role.
• Requires three (3) years of experience with automated Tableau dashboard creation for real-time fraud strategy monitoring.
• Requires three (3) years of experience with PySpark, Spark, and Hadoop ecosystems.
• Requires three (3) years of experience with root cause analysis and detection of fraud reversal patterns in payment systems.
• Requires three (3) years of experience with automation of batch data workflows using shell scripting.
• Requires three (3) years of experience with stakeholder management for cross-functional fraud risk initiatives.
• Requires three (3) years of experience with fraud risk management across banking products.
• Requires three (3) years of experience with Python, MS Excel, Tableau visualizations, SAS programming, and SQL query design.
• Requires two (2) years of experience with application fraud detection leveraging third-party fraud scores.
• Requires two (2) years of experience with end-to-end model monitoring using AUC, KS, ROC, Decile plots, and Gain charts.
• Requires two (2) years of experience with development and tracking of fraud Key Risk Indicators (KRIs).
• Requires two (2) years of experience with integration and interpretation of third-party fraud scores.

• Identify fraud trends and investigate suspicious behavior using various data sets.
• Detect out-of-pattern money movement transactions, including debit cards and wire transfers.
• Combine internal data with external intelligence to detect fraud early in the fraud lifecycle.
• Create solutions to improve existing controls based on identified trends.
• Develop effective solutions to enhance efficiency using analytical techniques and forecasting.
• Create rules in the rule's engine and conduct pre- and post-production testing.
• Partner with the Data Science team to develop fraud risk models.
• Use statistical methods to analyze data and generate business reports.
• Communicate trends, findings, proposals, and solutions to management and stakeholders.
• Measure performance using appropriate tools and techniques.
• Generate suspicious activity reports and risk management reports for management.
• Recommend or introduce new tools for fraud detection, prevention, and reporting.
• Design fraud strategy for new product launches by defining risk thresholds.

• Morgan Stanley offers extensive benefits that support employees’ careers, health, finances, and families, including top-tier medical coverage, mental health support, generous parental leave, fertility and family-building benefits, and robust retirement and stock purchase plans. Employees also gain access to continuous learning and networking opportunities, volunteer and giving programs aligned with the firm’s values, and hundreds of lifestyle perks like discounted products, cultural and entertainment tickets, and commuter savings.