Fraud & Risk Data Analyst Fintech & Data Insights *** Direct End Client ***

Staff Fraud & Risk Analyst Fintech & Data Insights

As a Fraud & Risk Data Analyst, you ll work at the intersection of analytics, compliance, and product innovation. This role is part of a dynamic Risk Insights and Experimentation team that influences billions of dollars in transactions annually. You ll partner with cross-functional teams to uncover insights, design experiments, and shape strategies that drive secure, scalable growth.

Domain expertise in Security, Risk & Fraud in Fintech space (consumer Lending, Fraud & Risk Policy, Compliance, Marketing, Product, Finance is required)

Key Responsibilities:

• Deliver clear, persuasive insights to senior leadership through data storytelling and executive-ready reports.
• Build intuitive dashboards and visualizations that guide strategic and operational decisions.
• Design and interpret A/B tests to optimize product performance and risk strategies.
• Collaborate with product, compliance, finance, and data science teams to define scalable analytics frameworks.
• Analyze large-scale transactional and behavioral data to detect trends, anomalies, and fraud patterns.
• Evaluate compliance effectiveness and recommend improvements to onboarding and remediation flows.
• Translate ambiguous business questions into structured analytical approaches using SQL, Python, and visualization tools.
• Investigate root causes of performance gaps and propose timely corrective actions.
• Maintain clean, reliable data pipelines and address data quality issues proactively.

Qualifications:

• 6+ years in analytics, data science, or decision strategy roles, ideally in Financial Services or Fintech.
• Advanced SQL skills and working knowledge of Python for data manipulation and automation.
• Experience with data visualization tools (Tableau, Quicksight, Qlik) and dashboard development.
• Strong understanding of A/B testing principles and experimental design.
• Proven ability to influence decisions through data-driven recommendations.
• Excellent communication skills for translating complex data into actionable insights.
• Bachelor s degree in a quantitative field (Economics, Math, Science) or equivalent experience.

fraud analyst, risk analyst, fintech analytics, SQL, Python, A/B testing, data visualization, Tableau, Quicksight, Qlik, compliance analytics, risk management, dashboard development, data science, financial services, experimentation, policy analytics, fraud detection, risk strategy, KPIs, OKRs, data storytelling