About the Role:
We are seeking a highly skilled and strategic Staff Data Analyst to join our Fraud and Risk team. In this role, you will play a key part in identifying, analyzing, and mitigating fraudulent activity across our platform. You will collaborate with cross-functional teams including Data Science, Risk Operations, Product, and Engineering to develop fraud detection strategies, monitor emerging patterns, and improve risk models.
This is a high-impact role where your insights will directly influence financial safety, operational efficiency, and customer trust.
Key Responsibilities:
- Analyze large-scale transactional and behavioral data to identify fraudulent patterns and trends
- Develop and maintain dashboards, fraud KPIs, and early warning systems using BI tools (e.g., Looker, Tableau, Power BI)
- Collaborate with engineers and data scientists to build and enhance real-time risk models and rules
- Conduct deep-dive investigations into fraud cases and generate actionable insights
- Partner with Product and Risk Ops to evaluate the impact of fraud controls and recommend improvements
- Own and maintain datasets, data pipelines, and documentation relevant to fraud analytics
- Present findings and strategic recommendations to senior leadership and cross-functional stakeholders
Required Qualifications:
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Economics, or a related field
- 5–8 years of experience in data analytics with a focus on fraud, risk, trust & safety, or payments
- Strong SQL skills and experience working with large datasets in production environments
- Proficiency with statistical tools and programming languages (Python, R, Spark, etc.)
- Familiarity with fraud detection techniques, rule-based systems, and model performance tracking
- Strong business acumen, communication, and data storytelling skills
Preferred Qualifications:
- Experience in fintech, e-commerce, digital payments, or financial services
- Knowledge of machine learning model evaluation and fraud scoring systems
- Experience working with real-time detection systems or event-streaming platforms (e.g., Kafka, Flink)
- Familiarity with regulatory risk and compliance standards (e.g., AML, KYC)
What We Offer:
- Competitive salary with equity or bonus potential
- Health, dental, vision, and life insurance
- Remote/hybrid flexibility
- Generous paid time off and wellness days
- Budget for professional development and certifications
- A mission-driven, high-growth environment where your work matters
How to Apply:
📩 Send your resume and a brief cover letter to: careers@[yourcompany].com
Subject: Staff Data Analyst – Fraud & Risk – [Your Name]
🗓️ Application Deadline: Open until filled (applications reviewed on a rolling basis)