Senior Data Analyst, Risk & Fraud

Overview

As a Senior Analyst on the Trust and Safety Analytics team, you will play a critical role in identifying, analyzing, and operationalizing key data signals to help Intuit prevent fraud, protect customers, and enforce acceptable use of products and services. You will apply strong analytical and technical skills to support and scale risk detection tools, monitoring processes, and mitigation strategies across Trust & Safety. This role partners closely with Product, Engineering, and Operations teams to deliver insights that drive data-informed decisions and measurable risk reduction.

Responsibilities

• Partner with Engineering and Product teams to support the design, implementation, and maintenance of analytics tools, dashboards, and data pipelines that enable effective fraud and risk monitoring.
• Analyze large, complex datasets to identify trends, anomalies, and emerging fraud patterns, translating findings into actionable recommendations.
• Contribute to the ongoing improvement of Trust & Safety platforms, including monitoring performance metrics, assessing platform health, and identifying risk gaps or degradation.
• Design and maintain dashboards and reporting (e.g., Tableau) to track fraud performance, operational efficiency, and risk exposure.
• Ensure data quality and reliability by performing validation, testing, and monitoring of analytics outputs; proactively identify and escalate issues.
• Support incident analysis and investigations by using data to identify root causes, quantify impact, and recommend mitigation actions.
• Stay current on fraud trends, AI-driven abuse, and industry best practices, incorporating new insights into analyses and detection strategies.
• Clearly communicate insights to both technical and non-technical stakeholders, influencing decisions through data-backed storytelling.
  
  

• Minimum 4 years of experience in analytics, risk management, or security roles within the fintech, eCommerce, technology, or cybersecurity industries
• Experience with anomaly detection, predictive modeling, or fraud risk strategies
• A solid understanding of fraud prevention, and AI-driven risks in the current industry landscape
• Strong proficiency in Python/SQL for data querying, analysis, and visualization
• Hands-on experience with Business Intelligence tools like Tableau
• Familiarity or prior experience with Generative AI models is a strong plus
• An educational background in Mathematics, Statistics, Computer Science, or equivalent field (Bachelor’s degree required).
• Demonstrated ability to deliver impactful analytics and insights in complex, fast-paced environments
• Experience in analyzing large datasets, identifying trends, and drawing actionable conclusions
• Comfortable working independently while collaborating effectively across internal teams to drive alignment and solutions
• Strong communication skills, with the ability to articulate complex findings to technical and non-technical stakeholders alike
• Attention to detail and a strategic mindset