PayPal is looking to leverage advanced machine learning and cutting-edge research to design innovative solutions that streamline compliance processes, strengthen risk mitigation, and empower PayPal to deliver a secure, trusted, and seamless financial experience worldwide, by ensuring adherence to a complex and evolving landscape of local and global regulations.
Requirements
- Strong theoretical foundation in ML algorithms, optimization, and statistical learning theory.
- Demonstrated ability to implement and evaluate ML models using Python and libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch.
- Experience conducting independent research, with publications in relevant ML/AI conferences or journals (preferred).
- Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, or a related field.
- Must be enrolled in a PhD program at an accredited university, returning to studies after the internship.
- Must reside in the U.S. during the program.
- Must be authorized to work in the U.S. for the duration of the internship.
Responsibilities
- Conduct applied research in machine learning and AI, focusing on novel methods for fraud detection, AML/KYC, regulatory reporting, and risk modeling.
- Investigate and prototype cutting-edge algorithms (e.g., deep learning, graph neural networks, reinforcement learning, generative models) to solve high-impact financial security problems.
- Collaborate with engineers, data scientists, and domain experts to translate business and regulatory needs into scalable ML frameworks.
- Perform advanced data analysis and experimentation to evaluate robustness, fairness, and interpretability of models in sensitive financial contexts.
- Contribute to the design and documentation of research-driven ML pipelines that emphasize reproducibility, scalability, and rigor.
- Disseminate findings through technical reports, internal presentations, and stakeholder discussions, demonstrating both theoretical and practical value.
- Explore emerging areas such as NLP for regulatory text analysis, graph learning for transaction networks, and causal inference in compliance and risk systems.
Other
- This is a Summer 2026 PhD Internship (Spring and Fall sessions are not available).
- Excellent communication and collaboration skills, with the ability to present research to both technical and non-technical audiences.
- Highly motivated, curious, and proactive in exploring new research directions.
- PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law.
- In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities.
