OverviewPayPal is seeking a senior machine learning engineer within Global Fraud Prevention to lead data-driven initiatives that enhance fraud detection and prevention. You will design and implement scalable machine learning data pipelines, ensure high data quality and integrity, develop and deploy production-grade solutions, and mentor junior team members. Your work will contribute to smarter, faster, and more reliable risk decisions across PayPal’s global platform.Essential ResponsibilitiesDesign and implement holistic, data-driven solutions to support PayPal’s global financial and fraud risk objectives.Partner with product and platform engineering teams to build cutting-edge, scalable, and secure ML-based products that enhance global customer experiences.Collaborate with data engineering and analytics teams to ensure reliable, high-quality training data and robust monitoring infrastructure.Develop and maintain production-level data pipelines, machine learning algorithms, and advanced statistical models.Utilize large-scale datasets for exploratory data analysis and feature engineering to drive strategic decisions.Ensure data integrity, fairness, and explainability in deployed ML systems through rigorous testing, validation, and bias detection practices.Communicate insights and progress to stakeholders and senior leadership through clear visualizations and narratives.Lead and mentor a team of data scientists and ML engineers, fostering innovation in ML techniques including supervised/unsupervised learning, reinforcement learning, and deep learning.Qualifications and Requirements8+ years of experience in relevant roles (e.g., data scientist, data analyst, statistician, decision scientist, risk management, etc.).Strong proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).Experience with LLMs, prompt engineering, RAG pipelines, or AI agents is a plus.Deep understanding of root cause analysis, anomaly detection, or incident forensics.Proven ability to translate business problems into data science solutions.Excellent communication skills and collaborative mindset; quick learner with broad knowledge and problem-solving abilities.Bachelor’s or Master’s in Computer Science, Statistics, Engineering, or related field; PhD a plus.About PayPal and CompliancePayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.Work Model and BenefitsPayPal’s balanced hybrid work model offers 3 days in the office and 2 days flexible work location. We offer benefits to support financial, physical, and mental health, including options for health and life insurance. To learn more about our benefits, visit https://www.paypalbenefits.com.Diversity, Inclusion, and BelongingPayPal is committed to equal employment opportunity and to creating an environment where everyone can do their best work with a sense of purpose and belonging. We provide reasonable accommodations for qualified individuals with disabilities. For general inquiries, please contact paypalglobaltalentacquisition@paypal.com. We are dedicated to fostering an inclusive culture that reflects the diverse merchants, consumers, and communities we serve.REQ ID R0128057
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