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Senior Fraud Strategy Data Analyst - Rippling
Data Analyst
Senior analyst responsible for designing and implementing data‑driven fraud strategies, building predictive models, and delivering actionable insights using SQL, Python, and visualization tools to protect financial and HR systems.
About the role
Key Responsibilities
- Develop and maintain fraud detection models using statistical and machine‑learning techniques.
- Analyze large‑scale HR, payroll, and finance datasets to identify risk patterns and emerging threats.
- Design dashboards and visual reports that communicate findings to cross‑functional stakeholders.
- Collaborate with engineering and product teams to integrate fraud controls into core platforms.
- Continuously monitor model performance, conduct root‑cause analysis, and iterate on solutions.
Requirements
- 5+ years of experience in data analysis, fraud analytics, or risk engineering.
- Proficiency in SQL and Python for data extraction, transformation, and modeling.
- Strong background in statistical modeling, hypothesis testing, and predictive analytics.
- Experience building data visualizations and dashboards (e.g., Tableau, Looker, Power BI).
- Excellent communication skills and ability to translate complex findings into actionable business recommendations.