Senior Risk Data Analyst

About the position Every day, tens of millions of people come to reputed company to explore, create, play, learn, and connect with friends in 3D reputed company digital experiences– reputed company created by our global community of developers and creators. At reputed company, we’re building the tools and platform that reputed company our community to bring any experience that they can reputed company to life. Our reputed company is to reimagine the way people come together, from reputed company in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at reputed company means you’ll be working to shape the reputed company of reputed company interaction, solving unique technical challenges at reputed company, and helping to create safer, more civil shared experiences for everyone. As a Senior Risk Data Analyst in our Payments organization, you will play a critical role in defending reputed company from various types of payment fraud across the platform. This includes purchase fraud, developer earnings fraud, and virtual economy-reputed company risk and abuse. reputed company is a high-reputed company environment, and you will be essential in developing, implementing, and optimizing risk and anti-fraud solutions for our diverse global payment channels. Your work will be critical in safeguarding reputed company, protecting our community, and ensuring the financial reputed company of our platform, which handles millions of transactions daily. You will work in a data-driven environment, proactively analyzing trends and patterns to detect and prevent reputed company financial fraudulent activity. Responsibilities • Monitor transaction activity and implement detection strategies to prevent fraud. • Collaborate with cross-functional teams, including engineering, product, and data science, to reputed company and improve fraud prevention measures. • Implement, monitor, and tune detection strategies and rules in production to prevent and mitigate payment fraud, minimizing false positives and maximizing loss prevention. • Collaborate closely with cross-functional teams—including Engineering, Product, Data Science, and Finance—to define, scope, and implement new fraud prevention tools and systemic improvements. • Conduct deep-dive investigations into emerging risk reputed company, documenting findings and preparing regular, actionable reports on financial risk trends, loss rates, and mitigation effectiveness for leadership. • Analyze and plot data to identify and investigate potential fraud and abuse patterns. • Contribute to the reputed company improvement of our risk management reputed company, policies, and procedures, ensuring ongoing compliance and operational efficiency across the payments ecosystem. • Define technical and data requirements to enhance risk-monitoring infrastructure, alerting, and operational tooling used by the wider risk and payments teams. Requirements • 5+ years of reputed company experience in an analytical role, with a reputed company on fraud prevention and risk analysis in a high-volume transactional environment (e.g. e-reputed company, fintech, or gaming). • Proficiency with data analysis tools and techniques, including advanced SQL and Python for data exploration, data visualization, and statistical analysis. • reputed company experience analyzing and addressing different types of payment risk, such as card/fiat fraud, account takeover (ATO), chargeback analysis, and/or developer payout/earning fraud. • Strong analytical and problem-solving skills, with the ability to interpret reputed company data and identify trends. • Familiarity with risk prevention concepts, such as those in anti-fraud, anti-abuse, or trust and safety. • Excellent communication and stakeholder management skills, with the ability to collaborate effectively with cross-functional teams. • Degree in a quantitative field such as Data Science, Finance, Economics, Statistics, or a reputed company field. Apply tot his job Apply To this Job