Manager Data Science - Fraud

ADP•Roseland, NJ

6d•Hybrid

About The Position

The Manager, Fraud Data Science is responsible for the performance, optimization, governance, and strategic expansion of ADP's Fraud Prevention Platform (FPP) and its associated fraud controls. This role owns the platform's real-time decisioning capabilities, including rules, models, decision strategies, third-party risk signals, AI-driven fraud detection capabilities, and control frameworks, ensuring they remain aligned with evolving fraud threats, enterprise risk appetite, client experience, and business growth objectives. FPP is a foundational component of ADP's fraud strategy, and this role will help rapidly mature the platform, broaden its use cases, and expand its capabilities across ADP. The Manager will partner closely with other leaders across Global Fraud Prevention, Global Security, business teams, and engineering to translate emerging threats, fraud intelligence, investigative insights, and operational feedback into scalable, production-ready fraud controls that address an ever-changing fraud risk landscape. This role will help shape the future direction of fraud decisioning at ADP. Success requires deep fraud prevention expertise, strong analytical and technical aptitude, experience with modern fraud decisioning platforms such as Feedzai, and the ability to balance fraud risk, client experience, operational efficiency, and business growth while continuously advancing the capabilities and adoption of ADP's enterprise fraud platform.

Requirements

A bachelor’s degree or equivalent practical experience in risk management, fraud analytics, data science, computer science, statistics, engineering, or a related field.
5-7+ years of experience in fraud prevention, fraud detection, risk decisioning, payments risk, identity risk, financial crime, or related discipline.
Experience with Python is required.
Experience working with real-time fraud decisioning, transaction monitoring, and risk orchestration platforms such as Feedzai, Alloy, Accertify, Socure, Transmit Security, or comparable solutions.
Demonstrated experience developing, tuning, testing, deploying, and monitoring fraud rules, decision strategies, risk scores, models, thresholds, and automated decisioning workflows.
Strong understanding of fraud typologies, detection techniques, identity and behavioral risk signals, evolving fraud threats, control design, false-positive management, and the relationship between fraud risk, customer experience, operational efficiency, and business growth.
Experience using data and performance metrics to evaluate fraud-control effectiveness, optimize decision strategies, and make risk-based recommendations.
Working knowledge of machine learning, statistical modeling, feature engineering, and model performance concepts, with experience translating analytical outcomes into operational fraud controls.
Strong proficiency in SQL and experience using analytics tools to perform data exploration, performance analysis, monitoring, and strategy optimization.
Excellent written and verbal communication skills, including the ability to explain complex fraud, analytics, and decisioning concepts to technical, business, and executive stakeholders.

Nice To Haves

Hands-on experience with Feedzai or a comparable real-time fraud decisioning platform, including rule configuration, model deployment, performance assessment, alert strategy, and production change management.
Experience scaling fraud decisioning capabilities across multiple products, channels, geographies, client segments, or business units.
Experience with model governance and validation practices, including champion/challenger testing, back-testing, simulation, performance monitoring, controlled rollouts, and ongoing strategy optimization.
Knowledge of payments fraud and related attack vectors, including account takeover, identity fraud, synthetic identity, first-party fraud, authorized fraud, and insider-enabled fraud.
Experience evaluating, onboarding, and measuring the effectiveness of third-party fraud, identity, device intelligence, behavioral risk, and consortium data providers, including proof-of-concept testing and signal optimization.
Working knowledge of APIs, data pipelines, real-time event processing, and platform integrations, with the ability to effectively partner with technology and engineering teams.
Experience applying AI/machine learning, graph analytics, network analysis, generative AI, or other advanced analytical techniques to fraud detection, risk management, and decisioning use cases.
Experience establishing fraud analytics standards, strategy governance frameworks, model governance practices, and decisioning best practices within a large enterprise environment.
Experience in financial services, payments, payroll, fintech, e-commerce, or another high-volume transaction environment.
Advanced degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, or a related quantitative field.
Demonstrated industry leadership through conference presentations, publications, patents, participation in fraud prevention forums, or contributions to the fraud, analytics, or risk management community.

Responsibilities

Own the strategy, performance, resilience, governance, and continuous evolution of the Fraud Prevention Platform (FPP) and its associated fraud controls.
Drive real-time fraud decisioning capabilities, including rules, models, AI-enabled detection capabilities, decision strategies, and third-party risk signals to address evolving fraud threats and business needs.
Monitor and optimize platform effectiveness through defined performance metrics, including fraud prevented, fraud losses, detection rates, false positive rates, operational impact, transaction volumes, and decision latency.
Establish model and decisioning performance, testing, and experimentation frameworks, including champion-challenger strategies, A/B testing, simulation, controlled rollouts, and post-implementation validation to measure effectiveness, improve business outcomes, and support risk-based decision making.
Develop closed-loop performance improvement processes that leverage fraud outcomes, production monitoring, threat intelligence, investigative findings, and operational feedback to continuously enhance fraud controls, decision strategies, and model performance.
Oversee platform health and resilience, including uptime, transaction processing, integrations, third-party data providers, and system performance. Establish processes to rapidly identify and resolve service disruptions, data issues, and degraded control performance.
Establish and maintain governance and change-management processes covering rule and model deployment, testing, approvals, documentation, monitoring, rollback, and ongoing performance management.
Evaluate, optimize, and govern third-party fraud, identity, device intelligence, behavioral, consortium, and other risk data sources to maximize decision quality, fraud detection effectiveness, and return on investment.
Define and execute the roadmap to mature FPP and expand fraud decisioning capabilities across products, channels, client segments, and enterprise use cases, including the adoption of advanced analytics and AI-driven capabilities.
Partner within the Global Fraud Prevention group as well as with Global Security, Engineering, and business stakeholders to translate fraud risks and requirements into scalable platform capabilities and measurable business outcomes.
Serve as the enterprise subject matter expert for FPP, advising stakeholders on platform capabilities, decisioning strategies, AI/ML-enabled functionality, integrations, data requirements, and fraud control effectiveness.