Director - Threat Detection Analyst

Morgan Stanley•Alpharetta, GA

About The Position

The Director role within Fraud Detection Analytics performs a critical function within the Fraud Department, in safeguarding the organization against diverse fraud risks. This position is responsible for designing, implementing, and overseeing advanced analytics strategies to detect and mitigate fraudulent activities across multiple payment channels and fraud typologies, including account takeover (ATO), deposit fraud, scams, and emerging schemes. The ideal candidate combines deep technical expertise with strategic vision and strong communication skills to drive cross-functional collaboration and deliver actionable insights.

Requirements

Minimum of 5+ years of experience in fraud analytics, financial crime, or risk management.
Bachelor's or Master's degree in Data Science, Computer Science, Finance, or related field.
Expert proficiency in SQL (including joins, subqueries, unions, temporary tables) for data extraction, analysis, and reporting.
Demonstrated experience designing and implementing fraud detection models, with a strong focus on account takeover, scam & first party fraud scenarios.
In-depth understanding of transaction exhaust methods (cryptocurrency, wires, ACH, Zelle, bill payments).
Strong analytical, problem-solving, and decision-making skills.
Excellent verbal and written communication skills, with the ability to present complex findings to non-technical audiences.
Experience working with large datasets and modern analytics tools (Python, R, Tableau, SAS).

Nice To Haves

Previous experience in banking, fintech, or payments industry.
Knowledge of regulatory requirements related to financial fraud and AML.
Familiarity with fraud monitoring tools and case management systems.
Ability to work in fast-paced, high-pressure environments and manage multiple priorities effectively.
Proven track record of leading successful fraud detection initiatives across multiple payment channels.
Advanced skills in statistical analysis and visualization platforms.
Experience collaborating with Data Science and Product teams to produce fraud risk models and meet business goals

Responsibilities

Develop and refine fraud detection controls and analytical frameworks targeting fraud risks such as ATO, deposit fraud, scams, and other typologies.
Monitor and analyze transaction channels (crypto, wire, ACH, Zelle, bill payments) for suspicious activity and emerging patterns.
Leverage data-driven insights by integrating internal data with external intelligence sources for proactive fraud detection.
Utilize SQL and advanced analytics to extract, analyze, and interpret large datasets to identify emerging fraud trends.
Apply predictive modeling, forecasting, and statistical methodologies to enhance operational efficiency and reporting.
Design and validate rules within the fraud rules engine, conducting rigorous pre- and post-production testing.
Continuously adjust controls based on observed trends to address evolving risks.
Identify automation opportunities to streamline manual processes related to data collection, metric calculation, and loss assessment.
Deliver business insights through dashboards and visualization tools (Tableau, SAS, Python, R) and produce on-demand reports.
Communicate key trends, findings, and actionable recommendations to management and stakeholders.
Prepare and present executive-level reports on suspicious activities and risk management.
Set and monitor KPIs for fraud detection, implementing mitigation strategies where needed.
Collaborate with Customer Service, Product Management, Engineering, and Data Science teams to enhance fraud detection tools and models.
Coordinate with Fraud Operations to align rule strategies with staffing resources.
Recommend and implement innovative technologies for fraud detection, prevention, and reporting.