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# Data Analyst

- **Company:** Robert Half
- **Location:** Franklin Township, NJ, United States
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Fraud Prevention and Detection
- **Published:** September 27, 2026
- **Apply:** https://dejobs.org/x/x/7FAA633284A4405B82A29251E482EDF5/job/

## About the Role

* Knowledge of suspected fraud indicators, fraud analytics techniques, and anti-fraud best practices.

 * Ability to interpret complex data and communicate findings clearly to both technical and non-technical audiences.

 * Experience supporting fraud investigation efforts through structured analysis and evidence-based insights.

 * Strong analytical mindset with attention to detail and the ability to recognize meaningful anomalies and trends.

 * Proficiency in working with data tools and reporting methods used to evaluate operational or fraud-related performance. Technology Doesn't Change the World, People Do.®

## Description

Description We are looking for a Data Analyst to join a team in Somerset, New Jersey and turn complex information into actionable insight that strengthens fraud detection efforts. This contract opportunity with potential for a permanent role is ideal for someone who combines strong analytical thinking with practical experience identifying suspicious patterns, supporting investigations, and improving anti-fraud decision-making. The role offers the chance to work closely with business partners to interpret data, surface risk trends, and contribute to a more proactive fraud strategy.

Responsibilities:

 * Examine large data sets to identify unusual activity, emerging fraud patterns, and indicators of potential risk.

 * Create reports, dashboards, and analytical summaries that help stakeholders monitor fraud performance and make informed decisions.

 * Partner with investigation and business teams to translate data findings into practical actions that support fraud prevention efforts.

 * Evaluate transactional and behavioral information to uncover trends, root causes, and opportunities to reduce exposure.

 * Support fraud investigations by gathering, organizing, and interpreting relevant data from multiple sources.

 * Refine analytical methods and detection approaches to improve accuracy, efficiency, and responsiveness in anti-fraud initiatives. Requirements * Hands-on experience in data analysis with a focus on fraud, risk, or investigative environments.


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