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# Data Analyst - Fraud Intelligence Team

- **Company:** Riskified Ltd.
- **Location:** Lisbon, OH, United States
- **Experience:** Experienced
- **Salary:** $37,000.0 - $42,000.0
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), SQL Databases, Transaction Data
- **Published:** September 18, 2026
- **Apply:** https://www.thejobnetwork.com/job/99a138f8-3d5e-4e69-91f7-a8c9570b01f7/data-analyst-fraud-intelligence-team

## About the Role

- 2-3+ years of relevant strong analytical experience with complex data
- 2+ years of hands-on work experience with SQL (must be proficient)
- Proven expertise in analysis tools such as R and Python 
- Experienced problem-solver with critical thinking skills
- Ability to work simultaneously on different tasks and lead multiple projects
- Full working proficiency (both written and verbal) in English
- Effective presentation skills, with a track record of client-facing experience
- Advantage - experience in fraud, payments, or ecommerce domains


## Description

We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day.

## **About the Role**

Join our Fraud Intelligence team at Riskified! As a Data Analyst on this team, you'll play a key role in helping us mitigate fraud and stay ahead of the fraudsters targeting our merchants. You'll research new and emerging fraud modus operandi (MOs), dive deep into transactional data, and help build and define the detection tools that power our fraud-prevention engine. This role sits at the core of Riskified's product and performance - the strength of our detection is a direct result of the work this team does every day.

## **What You'll Be Doing**

- Research and investigate new and evolving fraud modus operandi (MOs) across our merchant base
- Analyze large-scale transactional data using SQL (and R or Python) to uncover patterns, anomalies, and emerging fraud trends
- Collaborate with Data Science, Product, and Engineering to help build, define, and refine new fraud-detection tools 
- Translate research findings into actionable insights that directly improve detection accuracy and merchant performance
- Monitor and evaluate the performance of existing detection logic, flagging gaps or drift as fraud patterns evolve
- Document investigation findings and methodologies, strengthening the team's shared knowledge base
- Work cross-functionally with Risk Operations and Account Management to respond quickly to new fraud threats




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