Jobs at PayPal

Build and operate scalable, distributed payment-risk services supporting fraud detection and risk management across millions of transactions. Responsibilities include full SDLC ownership, backend Java development, API and microservice design, reliability and performance engineering, testing, delivery, and operations. The role advises management on project issues, guides junior engineers, makes technical decisions independently, and collaborates with product and technical leads to protect customers while maintaining seamless payments.

Lead marketing data science for Venmo Paid Marketing by developing measurement frameworks, analyzing media effectiveness, conducting incrementality and geo-experiments, applying attribution and marketing mix modeling, and optimizing audience, channel, budget, and campaign investments. The role requires translating complex analyses into actionable recommendations, collaborating with cross-functional teams, ensuring data quality, managing analytical projects, and mentoring junior data scientists.

Build and operate scalable, low-latency risk platform services for Venmo’s migration to PayPal’s HelixOS. Deliver solutions across the SDLC, develop Java microservices and REST APIs, integrate AI/ML and real-time inference, optimize cloud performance, and implement observability and auditing. Collaborate with Risk Strategy, Data Science, Product, and Architecture teams while guiding junior engineers and translating risk requirements into reliable technical capabilities.

Leads an SMB outbound sales team responsible for new-merchant acquisition, pipeline health, forecasting, conversion, productivity, and handoff to account management. Coaches sales hunters, identifies performance issues, partners with cross-functional teams to improve lead quality and volume, and designs measurable improvements to lead allocation, qualification, and handoff processes.

Generates and qualifies SMB sales opportunities through cold calling, email, and inbound leads. Conducts discovery, presents solutions, negotiates contracts, closes new business, maintains accurate pipeline forecasts, and collaborates across departments to improve offerings and customer satisfaction.

Owns the design, reliability, and operation of Java backend services supporting checkout, identity, commerce, payments, settlement, and payouts. Leads distributed-system design, migrations, incident response, observability, SLOs, and cross-team technical initiatives. Mentors engineers, reviews designs and code, coordinates knowledge transfer with Sweden, and partners with product, Finance, security, compliance, SRE, and platform teams.

Acts as a strategic revenue operations partner to sales leaders across international markets. Owns forecasting, territory and quota planning, sales cadence, QBR support, process improvement, change adoption, and complex deal escalation. Leads cross-market strategic projects involving compensation, seller productivity, onboarding, risk, and sales operations. Partners with sales, marketing, finance, risk, and global teams while influencing stakeholders without direct authority.

Leads data science projects, develops models and algorithms, analyzes complex datasets, and delivers insights for strategic decision-making. The role ensures data quality, supports experimentation and machine learning applications, collaborates with Product, GTM, Engineering, and data science teams, and mentors junior scientists. Responsibilities include translating analytical findings into business strategies, measuring portfolio performance, and presenting recommendations to senior management.

Drives new SMB sales through cold calling, email outreach, inbound lead response, discovery, solution presentation, contract negotiation, and closing. Maintains accurate sales pipelines, forecasts revenue, reports performance, and collaborates cross-functionally to address customer needs and improve offerings.

Provides strategic cybersecurity counsel to senior executives, leads multi-year security strategy, resolves high-impact security challenges, drives technology roadmaps, and guides teams toward innovative solutions aligned with business objectives.

Leads complex, enterprise-wide strategic programs from planning through execution. Responsibilities include developing budgets and timelines, coordinating cross-functional teams and contractors, managing risks and dependencies, resolving blockers, supporting executive decision-making, overseeing governance and reporting, improving program management practices, and enabling organizational change. The role requires strong stakeholder management, communication, business acumen, and the ability to influence without direct authority in a matrixed environment.

Owns an enterprise data platform serving customer, session, and transaction data across multiple brands. Defines product requirements, manages the roadmap, leads agile planning and delivery, and oversees migrations from legacy systems to a cloud-native platform. Uses platform health, adoption, data quality, performance, and budget metrics to prioritize work. Collaborates with engineering, architecture, governance, privacy, security, risk, and client teams to manage dependencies and deliver platform improvements.

Provides strategic legal and regulatory advice to senior management, assesses and manages enterprise legal risks, supports compliance, handles escalations, and develops forward-looking risk mitigation strategies. The role partners across the organization to advance business objectives, influence executive decision-making, adopt legal technologies and best practices, and provide industry leadership on emerging legal trends.

Manages multiple internal information systems and nontechnical projects from initiation through delivery. Develops program plans and budgets, coordinates cross-functional teams and contractors, identifies and mitigates risks, ensures timely and cost-effective completion, provides strategic guidance to project managers, maintains stakeholder relationships, and mentors junior project managers.

Develop, test, debug, and maintain scalable front-end and back-end software for PayPal payment platforms. Interns design and implement solutions, optimize databases, participate in code and design reviews, follow SDLC practices, collaborate with cross-functional teams, deploy changes, and help triage production issues.

Cybersecurity interns support application security and technology risk teams by testing security products, reviewing code, analyzing and remediating vulnerabilities, developing threat models, and improving security processes. They also assess risks and controls, support audits, document remediation activities, evaluate control weaknesses, and develop tools for risk management. Interns collaborate with engineers, security architects, product managers, auditors, and business stakeholders while learning cybersecurity and governance frameworks.

Data Scientist Interns analyze complex datasets, define metrics, conduct experiments, identify trends, and develop actionable recommendations for PayPal products. They collaborate with product, engineering, and data teams, improve data quality, communicate insights to technical and non-technical stakeholders, and contribute to end-to-end machine learning solutions while managing multiple projects.

Develop mobile applications for iOS and/or Android, writing clean code, testing and debugging applications, collaborating with cross-functional teams, deploying changes, and supporting production issue resolution. Interns will help build scalable payment experiences and distributed systems while applying mobile UI/UX, API, cloud, database, and asynchronous programming knowledge.

Conduct applied machine learning research, develop and evaluate models, analyze data, build production pipelines, monitor model performance, and communicate technical findings. Collaborate with engineers, data scientists, and product teams to create scalable solutions for compliance, risk mitigation, and secure financial services. The intern must be pursuing a PhD and returning to school in Fall 2027.

Supports the development of machine learning models and algorithms through data preparation, experimentation, evaluation, optimization, and deployment. Collaborates with engineers, data scientists, and product teams on scalable ML pipelines and production model monitoring. Writes maintainable code, documents technical decisions, participates in reviews, and explores emerging machine learning techniques for PayPal products.