Data Scientist 2

**The Company**

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do - and they push us to ensure we take care of ourselves, each other, and our communities.

Job Description Summary: What you need to know about the role
- Data scientists are highly motivated team players with strong analytical skills who specialize in creating, driving and executing initiatives to mitigate fraud on PayPal’s platform and improve the experience for PayPal’s hundreds of millions of customers, while guaranteeing compliance with regulations. Meet our team Data scientists in the Fraud Risk team are problem solvers suited to approach varied challenges in complex big data environments. Our core goals are to enable seamless and delightful experiences to our customers, while preventing threat actors from accessing customers’ financial instruments and personal information. As part of our day-to-day job, we are collaborating with a wide variety of partners: product owners, data scientists, security experts, legal consults, and engineers, to bring our data science insights to life, impacting the experience and security of millions of customers around the globe.

**Job Description**:
**Your way to impact**

Data scientists deeply understand PayPal’s business objectives, as their impact on PayPal’s top and bottom lines is immense. As a data scientist, you will develop key AIML capabilities, tools, and insights with the aim of adapting PayPal’s advanced proprietary fraud prevention and experience mechanisms and enabling growth.

**Your day to day**

Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets.

**What do you need to bring-**
- Strong proficiency in Python for data analysis, machine learning, and automation.
- Solid understanding of supervised and unsupervised AI/machine learning methods (e.g., XGBoost, LightGBM, Random Forest, clustering, isolation forests, autoencoders, neural networks, transformer-based architectures).
- Experience in payment fraud, AML, KYC, or broader risk modeling within fintech or financial institutions.
- Experience developing and deploying ML models in production using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar.
- Hands-on experience with LLMs (e.g., OpenAI, LLaMA, Claude, Mistral), including use of prompt engineering, retrieval-augmented generation (RAG), and agentic AI to support internal automation and risk workflows.
- Ability to work cross-functionally with engineering, product, compliance, and operations teams.
- Proven track record of translating complex ML insights into business actions or policy decisions.
- BS/BA degree with 5+ yea