Sr. Fraud Strategy Data Analyst

About the role

As the Senior Fraud Strategy Data Analyst, you will play a key role in protecting our organization's integrity by analyzing fraud risk across the platform and supporting the development of strategies to address account takeover (ATO) fraud, suspicious activity detection, and fraud risk controls related to product access and adverse actions. You will leverage your analytical skills and business acumen to surface insights, build detection logic, and partner with data science, security, product, and compliance teams to strengthen our fraud prevention posture.

• Analyze platform fraud trends and contribute to fraud risk control strategies for ATO, suspicious activity detection, and financial product access.
• Use SQL and Python to perform complex data analysis, build dashboards, and generate insights that inform risk management decisions and strategy development.
• Help design, test, and refine fraud detection rules and algorithms to identify and mitigate suspicious activities across the platform.
• Support the implementation of policies and controls that prevent unauthorized account access and adverse actions, partnering with security engineering on tracking and detection.
• Conduct data‑driven investigations to uncover fraud patterns, measure control performance, and recommend optimizations to detection methodologies.
• Perform cost‑benefit and impact analyses that balance fraud prevention with user experience and operational efficiency.
• Collaborate across teams — including Security, Sales, Customer Service, and Compliance — to support fraud monitoring and response workflows.
• Partner with R&D on requirements for fraud detection and investigation tooling, providing data‑driven feedback to ensure they meet evolving business needs.

• 4+ years of experience in fraud prevention and detection, risk analytics, or a closely related analytical role, ideally within the financial technology sector.
• Bachelor's degree in a relevant field (e.g., Mathematics, Statistics, Computer Science, Economics, or a related discipline); a Master's degree is preferred.
• Strong expertise in data analysis with demonstrated proficiency in SQL and Python for fraud detection, investigation, and strategy support.
• Solid understanding of account takeover risks, suspicious activity patterns, and fraud prevention methodologies.
• Familiarity with industry-leading tools and third‑party risk vendors for fraud detection and analysis.
• Working knowledge of industry regulations and compliance requirements related to fraud risk management.
• Excellent communication skills, with the ability to translate complex data insights into clear recommendations for technical and non‑technical stakeholders.
• Strong attention to detail, intellectual curiosity, and a bias toward action in ambiguous problem spaces.

Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process.

To request a reasonable accommodation, please email

Rippling highly values having employees working in‑office to foster a collaborative work environment and company culture. For office‑based employees (employees who live within a defined radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.