Staff Data at PayPal Inc. San Jose, California

Staff Data Scientist

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 to help them 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 Summary: We are seeking a Staff Data Scientist to lead the design, development, and deployment of advanced AI systems, including Retrieval-Augmented Generation (RAG), semantic knowledge bases, and MCP (Model Context Protocol) server ecosystems. This role requires deep technical expertise combined with architectural leadership, ownership of end-to-end AI systems, and the ability to drive best practices across teams. You will play a critical role in shaping our AI strategy and delivering scalable, production-grade intelligent systems.

Job Description: Essential Responsibilities:

• Lead and manage data science projects, ensuring timely delivery and alignment with business goals.
• Develop and maintain data models, algorithms, and reporting systems to support data analysis and decision-making.
• Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives.
• Collaborate with cross-functional teams to understand data needs and provide actionable insights.
• Ensure data quality and integrity through regular audits and validation processes.
• Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement.

Minimum Qualifications:

• 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.

Additional Responsibilities & Preferred Qualifications: Responsibilities:

• Lead the design and architecture of end-to-end AI systems, including: RAG pipeline, Semantic knowledge bases, Vector search and retrieval systems
• Define and implement best practices for LLM-based systems, including prompting, evaluation, and system design
• Architect, build, and scale MCP servers and integrate them into broader AI and product ecosystems
• Drive development of LLMOps frameworks, including evaluation, monitoring, and continuous improvement of AI systems
• Design and optimize retrieval pipelines, including embeddings, indexing, ranking, and hybrid search
• Mentor and guide junior data scientists and engineers on AI system design and statistical rigor
• Collaborate cross-functionally with engineering, product, and leadership to translate business problems into scalable AI solutions
• Establish metrics, experimentation frameworks, and statistical validation approaches for AI system performance

Required Skills & Qualifications:

• Experience leading large-scale AI initiatives or platforms
• Familiarity with fine-tuning techniques (LoRA, PEFT) and model customization
• Experience with multi-agent systems and orchestration frameworks
• Background in search, recommendation systems, or knowledge graphs
• Experience in enterprise or regulated environments (e.g., fintech)

AI / Systems Architecture:

• Deep expertise in: RAG architectures and retrieval systems, Semantic search and knowledge systems, Vector databases (Pinecone, Weaviate, FAISS, Chroma)
• Strong experience with LLMs (OpenAI, Anthropic, open-source models)
• Proven experience designing and scaling MCP servers or similar AI system infrastructure
• Experience with agent frameworks and tool/skill orchestration

LLMOps / Production Infrastructure:

• Strong experience launching production AI Agents systems, including:
• Experiment tracking and evaluation (LangSmith, Weights & Biases, MLflow)
• Observability and monitoring (latency, token usage, system reliability)
• Evaluation frameworks for RAG (faithfulness, hallucination detection, groundedness)

Embeddings & Retrieval Optimization:

• Deep understanding of embedding models and semantic similarity
• Expertise in improving retrieval quality via:
• Hybrid search (vector + keyword/BM25)
• Reranking models (Cohere Rerank, Hugging Face cross-encoders)
• Advanced chunking, indexing, and document processing strategies
• Proven ability to optimize end-to-end RAG system performance

Prompting & LLM Engineering Advanced expertise in:

• Prompt engineering and optimization
• Context design and grounding techniques
• Systematic evaluation and iteration of LLM outputs

Data Science & Statistical Leadership Strong foundation in:

• Probability and statistics
• Hypothesis testing and experimentation
• Causal inference and experimental design
• Experience defining metrics and evaluation frameworks for complex AI systems

Programming & System Design:

• Strong proficiency in Python
• Experience with:
• ML/AI frameworks (PyTorch, TensorFlow, Hugging Face)
• Data processing (Pandas, NumPy, Spark)
• Backend/API development (FastAPI or similar)
• Solid understanding of distributed systems and scalable architecture

What Success Looks Like:

• Architect and deliver scalable, production-grade AI systems
• Establish best practices for RAG, LLMOps, and retrieval optimization
• Drive measurable improvements in system accuracy, latency, and reliability
• Influence technical direction and elevate AI capabilities across the organization

Subsidiary: PayPal Travel Percent: 0 - The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Primary Location | Pay Range: San Jose, California | ($176,500.00 - $262,350.00 Annually) Additional Location(s) | Pay Range: No other locations are assigned to this requisition currently. Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable. PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit For the majority of employees, PayPal's balanced hybrid work model offers