Overview
PayPal 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 Responsibilities
* Design 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 Requirements
* 8+ 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 Compliance
PayPal 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 Benefits
PayPal’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 Belonging
PayPal 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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