Senior Data Analyst, Fraud and Identity

Details

• Ownership of Data Analysis & Visualization: Monitor and improve critical KPIs such as fraud costs, chargeback volume, fraud rates and revenue leakage.
• Strategic Communication: Regularly communicate outcomes and insights to cross-functional stakeholders, including senior leadership, to guide strategic decision-making for process and performance improvement.
• Development of Single Source of Truth (SSOT) Dashboards and Reporting Models: Work alongside DS & Broader Fraud & Identity analysts to implement robust models in DBT and Snowflake, and design dashboards that provide a unified view of business-critical Shopper fulfillment, Shopper Payment and PoS (point of sale) Checkout data. Work closely with Compliance and Legal teams to meet reporting requirements and successfully navigate audits
• Collaboration on Roadmaps: Work with Product, Data Science, and Xfn Analytics teams to understand growth and risk factors related to new and future fraud vectors.Operational Data Analysis: Analyze shopper behavioral signals to identify anomalous patterns indicative of fraud or policy abuse.
• A/B Testing & Experimentation: Design and conduct A/B and multivariate tests by developing test plans, defining success metrics, analyzing, and transforming data into actionable insights
• Xfn Collaboration: Collaborate with the Engineering and Product team to instrument new product features and ensure great event tracking and data integrity.
• Automation and Reporting: Build automated reporting systems to keep operations leaders informed of trends, variations, and opportunities across geographies and teams.
• Minimum 6 - 8 years of analytical experience, preferably in payments,fraud or identity domains
• Ability to Identify potential root causes contributing to potential change(s) in metrics and provide recommendation on mitigation strategy
• Strong analytical mindset with a track record of resolving complex transaction issues.
• High proficiency in SQL, with experience writing complex queries, joins, and optimizations.
• Experience with R/Python (fluency in at least one language preferred)
• Experience with analytical visualization tools such as Mode, Tableau, Looker, Periscope or similar tools
• Understanding of A/B testing and other forms of statistical analysis using statistical packages
• Extremely strong verbal and written communication skills, including the ability to synthesize complex topics and create compelling narratives for various audiences
• Ability to work effectively with internal stakeholders, including data scientists and data engineers. Work cross functionally with Product, Engineering, Operations to drive changes
• Excellent teamwork skills and desire to help others learn
• High level of accountability and ownership – driven and focused self-starter
• Strategic mindset – the ability to think ahead of where the company is at now
• Experience in e-commerce, CNP payments, finance, SaaS, digital goods or marketplace industry.
• Experience in driving understanding of customers and their interaction with products, through in-depth analyses of user behavior and engagement
• Experience in Fraud, Reconciliation, Identity or Transaction Risk field
• Experience working with authentication, anti-fraud systems and checkout, tools or vendors
• Advanced degree in statistics or other quantitative fields
• Experience with experimentation, Data modeling, ETL and data pipeline development experience
• Proficiency with AI tools (e.g., Claude, ChatGPT, Copilot) and a demonstrated ability to integrate them into day-to-day workflows.