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Salary: USD 125,000 - 145,000 / annual
Extend is a fintech platform revolutionizing the post-purchase experience for retailers through AI-driven solutions for customer service, returns management, fulfillment, and fraud detection. The company works with over 1,000 merchant partners across fashion, cosmetics, furniture, jewelry, electronics, and other industries.
The Fraud Intelligence team is the analytical backbone of Extend's post-purchase protection platform, turning signals from hundreds of millions of transactions into actionable insights that determine what fraud gets caught, stopped, or allowed through. This is a high-ownership role where your analysis directly protects retailers, builds customer trust, and impacts the company's bottom line.
In this position, you will analyze large-scale behavioral, transactional, and interaction data to uncover fraud and abuse signals. You'll apply business acumen to rapidly identify actionable insights, analyze fraud patterns, and validate hypotheses. You'll respond swiftly to emerging fraud threats by developing monitoring frameworks, dashboards, and mitigation solutions in collaboration with cross-functional teams. You'll evaluate the Fraud Ops AI review agent—assessing both the quality of case summaries and accuracy of recommended decisions—and translate findings into prompt, rule, and workflow improvements. You'll partner with the Machine Learning team to translate fraud pattern findings into model feature recommendations and provide feedback on model scoring based on investigation outcomes. Additionally, you'll participate in design and code reviews and mentor junior analysts on SQL and analysis best practices.
The work moves quickly: new fraud tactics emerge, you find them in the data, and you help shut them down. You'll work on the front line of how AI is changing fraud review, alongside Fraud Ops and the ML team, ensuring your analysis translates into material changes rather than just presentations.
REQUIREMENTS:
- 3+ years of experience in fraud analytics, ideally within e-commerce or retail
- Prior experience in a startup or high-growth environment preferred
- Bachelor's degree or higher in a quantitative field (Mathematics, Statistics, Computer Science, Engineering, Operations Research, Physics, or related)
- Strong grasp of core data science and analytics concepts, including statistical analysis, modeling, and data wrangling
- Proficiency in SQL and experience with Python (pandas, NumPy, scikit-learn, etc.)
- Experience evaluating or tuning automated decisioning systems (LLM-based or rules-based) is a plus
- Exceptional communication and stakeholder management skills with proven ability to work cross-functionally and influence outcomes
- High attention to detail, strong intellectual curiosity, and deep understanding of user behavior and fraud patterns
- Empathetic, humble, and collaborative team player
- Must be located within continental United States
