Sr Data Scientist

Experteer Overview In this Sr Data Scientist role, you apply advanced analytics to detect and prevent fraud in real time, transforming raw transactional data into actionable risk insights. You’ll design and validate statistical models, monitor fraud across payment ecosystems, and drive risk-minded product decisions. You’ll build dashboards and collaborate with product teams to support launches while evolving fraud defenses. The role offers a chance to shape PayPal’s risk framework at scale and mentor peers in cutting-edge techniques. Compensation / Benefits * Research multi-dimensional data sets to identify fraudulent activity in real time * Build, validate, and maintain statistical models for fraud detection * Develop real-time risk assessment solutions balancing loss, UX, and product KPIs * Conduct rigorous A/B tests to evaluate fraud controls and model enhancements * Create dashboards (Tableau/Power BI) for risk metrics and stakeholder insights * Perform root cause analysis of fraud cases and address systemic vulnerabilities * Partner with Product Management and business units on risk assessments for new launches * Translate risk requirements into technical specs for risk capabilities * Develop risk frameworks and documentation for consistent evaluation across products * Present analytical findings to senior leadership and translate concepts for non-technical audiences * Mentor junior analysts in advanced statistical techniques and fraud detection Tasks * Master’s degree in Data Science, Mathematics, or closely related field (or foreign equivalent) * 3 years of relevant experience in fraud detection, risk, or a related area * Experience performing root cause analysis on fraud within financial transaction systems * Proficiency in Python (NumPy, Pandas) for data processing and Scikit-learn for model development * Experience building Tableau dashboards for fraud risk KPIs * Strong SQL skills and experience with cloud-based data platforms and distributed data systems * Experience applying statistical models and running A/B tests for risk strategies * Knowledge of payment ecosystems and MANIC model in fraud contexts * Experience deploying machine learning models in real-time fraud detection (Python frameworks e.g., H2O) * Version control with GitHub and automation for scalable analytics Key requirements * balanced hybrid work model * healthcare coverage for you and family * generous paid time off * equitable benefits * financial security resources * career development and inclusive culture

• cases and address systemic vulnerabilities * Partner with Product Management and business units on risk assessments for new launches * Translate risk requirements into technical specs for risk capabilities * Develop risk frameworks and documentation for consistent evaluation across products * Present analytical findings to senior leadership and translate concepts for non-technical audiences * Mentor junior analysts in advanced statistical techniques and fraud detection Tasks * Master’s degree in Data Science, Mathematics, or closely related field (or foreign equivalent) * 3 years of relevant experience in fraud detection, risk, or a related area * Experience performing root cause analysis on fraud within financial transaction systems * Proficiency in Python (NumPy, Pandas) for data processing and Scikit-learn for model development * Experience building Tableau dashboards for fraud risk KPIs * Strong SQL skills and experience with cloud-based data platforms and distributed data aaaaaz _ * Experience applying statistical models and running A/B tests for risk strategies * Knowledge of payment ecosystems and MANIC model in fraud contexts * Experience deploying machine learning models in real-time fraud detection (Python frameworks e.g., H2O) * Version control with GitHub and automation for scalable analytics Key requirements * balanced hybrid work model * healthcare coverage for you and family * generous paid time off * equitable benefits * financial security resources * career development and inclusive culture