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# Data Analyst

- **Company:** Riskified Ltd.
- **Location:** Lisbon, OH, United States
- **Experience:** Experienced
- **Salary:** $37,000.0 - $42,000.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Fraud Prevention and Detection, Python (Programming Language), SQL Databases
- **Published:** September 11, 2026
- **Apply:** https://www.thejobnetwork.com/job/9a461370-4560-45c2-b85d-9d94fbdfe9f1/data-analyst

## 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

Join our global analytics team at Riskified! As a Data Analyst, you'll work directly with enterprise customers and be responsible for Riskified's customers' performance and online fraud prevention in real-time. You will own a major part in researching and investigating new online-fraud trends and stand at the forefront of Riskified's work. You'll leverage your analytical skills and knowledge of our product to provide meaningful insights to our merchants.

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

- Research and explore data, using high level analytical tools (R and SQL) in a high level technical environment
- Effectively communicate analytical insights and complex technical methodologies to both technical and non-technical audiences
- Collaborate with various teams within Riskified to optimize processes and meet customers' needs
- Engage with account managers, directly interface with clients, and deliver analytical insights to business questions
- Define and execute end-to-end technical solutions for fraud-prevention challenges
- Master the online fraud prevention domain through hands-on analysis of live data




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