Director, Data and Analytics Engineer

Morgan Stanley is a leading global financial services firm offering a wide range of investment banking, securities, investment, and wealth management services. The Firm's employees serve clients worldwide, including corporations, governments, and individuals from more than 1,200 offices in 43 countries. In Technology, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities.

About the role

Morgan Stanley Services Group, Inc. is seeking a Director, Data and Analytics Engineer in Jersey City, NJ to identify fraud trends, investigate suspicious behavior and identify significant insights from different sets of data. Work with data to detect out-of-pattern money movement transactions, such as, but not limited to debit cards, Wire Transfers, and trading. Combine internal data with external intelligence to detect fraud as early in the fraud lifecycle as possible. Create solutions to the trends identified by improving existing or creating new controls. Create effective solutions in improving efficiency using different analytical techniques and forecasting. Create rules in the rule's engine and conduct pre- and post-production testing to ensure effectiveness. Partner with the Data Science team to develop fraud risk models. Use statistical methods to analyze data and generate useful 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 used for fraud detection, prevention and reporting activities. Creation of fraud strategy design for new product launches by defining risk thresholds.

Responsibilities

• Automated Tableau dashboard creation for real-time fraud strategy monitoring;
• PySpark;
• Spark;
• Hadoop ecosystems;
• Root cause analysis and detection of fraud reversal patterns in payment systems;
• Automation of batch data workflows using shell scripting;
• Stakeholder management for cross-functional fraud risk initiatives;
• Fraud risk management across banking products, including payment systems, transaction monitoring, and retail lending;
• Python;
• MS Excel;
• Tableau visualizations for KPI tracking and strategy creation in fraud management;
• SAS programming for risk reporting in fraud analytics;
• SQL query design for fraud data aggregation and transformation.

Requirements

• Three (3) years of experience in the position offered or three (3) years as an Associate, Senior Consultant, or a related role;
• Three (3) years of experience with the following skills:

• Automated Tableau dashboard creation for real-time fraud strategy monitoring;
• PySpark;
• Spark;
• Hadoop ecosystems;
• Root cause analysis and detection of fraud reversal patterns in payment systems;
• Automation of batch data workflows using shell scripting;
• Stakeholder management for cross-functional fraud risk initiatives;
• Fraud risk management across banking products, including payment systems, transaction monitoring, and retail lending;
• Python;
• MS Excel;
• Tableau visualizations for KPI tracking and strategy creation in fraud management;
• SAS programming for risk reporting in fraud analytics;
• SQL query design for fraud data aggregation and transformation.

Qualifications

• Two (2) Years Of Experience With Application fraud detection leveraging third-party fraud scores and custom rule engines;
• End-to-end model monitoring using AUC, KS, ROC, Decile plots, and Gain charts for fraud analytics;
• Development and tracking of fraud Key Risk Indicators (KRIs) for retail lending portfolios;
• Integration and interpretation of third-party fraud scores including Experian FraudNet, EWS, and Sentilink.

Skills

• Automated Tableau dashboard creation for real-time fraud strategy monitoring;
• PySpark;
• Spark;
• Hadoop ecosystems;
• Root cause analysis and detection of fraud reversal patterns in payment systems;
• Automation of batch data workflows using shell scripting;
• Stakeholder management for cross-functional fraud risk initiatives;
• Fraud risk management across banking products, including payment systems, transaction monitoring, and retail lending;
• Python;
• MS Excel;
• Tableau visualizations for KPI tracking and strategy creation in fraud management;
• SAS programming for risk reporting in fraud analytics;
• SQL query design for fraud data aggregation and transformation.

Benefits

The successful candidate may be eligible for an annual discretionary incentive compensation award. The successful candidate may be eligible to participate in the relevant business unit’s incentive compensation plan, which also may include a discretionary bonus component. Morgan Stanley offers a full spectrum of benefits, including Medical, Prescription Drug, Dental, Vision, Health Savings Account, Dependent Day Care Savings Account, Life Insurance, Disability and Other Insurance Plans, Paid Time Off (including Sick Leave consistent with state and local law, Parental Leave and 20 Vacation Days annually), 10 Paid Holidays, 401(k), and Short/Long Term Disability, in addition to other special perks reserved for our employees.

Pay

$140,000 - $165,000 /Yr.

Schedule

Telecommuting permitted up to Two (2) days per week.