PayPal
Director, SE Data & Automation
PayPal, San Jose, California, United States, 95199
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:
Successful candidate will oversee teams focused on building the systems and tools for PayPal’s Sales, Service, and Support teams to operate at scale. This role will collaborate with cross-functional partners to develop the data infrastructure, tooling, and systems that help visualize data and trends on consumer and merchant satisfaction, growth, churn, and operational efficiency and profitability; these partners include segment Commercial, Operations, Product, and Engineering leads, and other cross-functional stakeholders.
Job Description:
Summary:
PayPal’s Service Experience organization is focused on winning, keeping, delighting, and doing more for the 430M consumers and merchants on PayPal’s platform. This team has end-to-end accountability for driving delightful and profitable support and service experiences in markets around the world. The team ensures seamless execution, drives profitable growth, and supports the global sales and distribution of PayPal's products and services.
Reporting to PayPal’s Senior Director of Service Experience and Business Intelligence, the Director, Data & Automation, will oversee teams focused on building the systems and tools for PayPal’s Sales, Service, and Support teams to operate at scale. This role will collaborate with cross-functional partners to develop the data infrastructure, tooling, and systems that help visualize data and trends on consumer and merchant satisfaction, growth, churn, and operational efficiency and profitability; these partners include segment Commercial, Operations, Product, and Engineering leads, and other cross-functional stakeholders.
The Director, Data & Automation will lead strategic, high-impact projects including the development of next-generation consumer / merchant support and service capabilities powered by machine-learning and generative AI. This role will focus on developing automated systems that visualize data, empower stakeholders, and help teams win at scale. This role is expected to possess both technical and commercial perspective and will play an integral role in leading projects from idea generation to implementation. Key Responsibilities: Collaborate with cross-functional partners on the development and deployment of next-gen approaches to enhancing service, support, and sales (e.g., automation, generative AI tools, LLMs, etc.) Develop machine learning models to understand customer trends, build customer cohorts, and enable personalized experiences Lead, develop, and inspire a team of Data Scientists and Data Engineers focused on acquiring, organizing and making sense of information at scale Own the development and maintenance of CRM systems and dashboards that power commercial, technical, and operational teams with insights across global markets. Use data to drive operational efficiency, improve funnel conversion and retention, and identify opportunities to enhance the customer journey. Partner with Risk, Engineering, Sales, and Operations owners to proactively enhance the onboarding experience, lower acquisition costs, and drive improved product engagement, loyalty, and retention through personalization (e.g., customer segmentation). Contribute to service and support strategies that integrate advanced technology and automation to improve platform efficiency for merchant / consumer support and services (e.g., self-service tools, chatbots, generative AI, internal tools, etc.). Collaborate with executive-level stakeholders on the evaluation, development, and execution of product launches and marketing campaigns designed to increase share-of-wallet, reduce churn, drive retention, and improve loyalty. Oversee evaluation of the impact of product investments on ROI, including impact on revenue, unit economics, and overall consumer and merchant experience. Qualifications: Graduate degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, electrical engineering, mathematics, physics) with 10+ years of related professional experience (or PhD with 8+ years). 10+ years of experience managing AI and / or ML teams, working collaboratively with engineering and cross-functional partners, and / or guiding data-influenced product planning, prioritization, and strategy development. Demonstrated experience in hiring, retaining, and scaling diverse, geographically dispersed, high-performing teams. Expertise in ML with hands-on experience in building and implementing large-scale predictive models. Familiarity with ML modelling techniques (e.g., deep learning, gradient boosting, graph, NLP/LLM, regression, clustering etc.).
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Reporting to PayPal’s Senior Director of Service Experience and Business Intelligence, the Director, Data & Automation, will oversee teams focused on building the systems and tools for PayPal’s Sales, Service, and Support teams to operate at scale. This role will collaborate with cross-functional partners to develop the data infrastructure, tooling, and systems that help visualize data and trends on consumer and merchant satisfaction, growth, churn, and operational efficiency and profitability; these partners include segment Commercial, Operations, Product, and Engineering leads, and other cross-functional stakeholders.
The Director, Data & Automation will lead strategic, high-impact projects including the development of next-generation consumer / merchant support and service capabilities powered by machine-learning and generative AI. This role will focus on developing automated systems that visualize data, empower stakeholders, and help teams win at scale. This role is expected to possess both technical and commercial perspective and will play an integral role in leading projects from idea generation to implementation. Key Responsibilities: Collaborate with cross-functional partners on the development and deployment of next-gen approaches to enhancing service, support, and sales (e.g., automation, generative AI tools, LLMs, etc.) Develop machine learning models to understand customer trends, build customer cohorts, and enable personalized experiences Lead, develop, and inspire a team of Data Scientists and Data Engineers focused on acquiring, organizing and making sense of information at scale Own the development and maintenance of CRM systems and dashboards that power commercial, technical, and operational teams with insights across global markets. Use data to drive operational efficiency, improve funnel conversion and retention, and identify opportunities to enhance the customer journey. Partner with Risk, Engineering, Sales, and Operations owners to proactively enhance the onboarding experience, lower acquisition costs, and drive improved product engagement, loyalty, and retention through personalization (e.g., customer segmentation). Contribute to service and support strategies that integrate advanced technology and automation to improve platform efficiency for merchant / consumer support and services (e.g., self-service tools, chatbots, generative AI, internal tools, etc.). Collaborate with executive-level stakeholders on the evaluation, development, and execution of product launches and marketing campaigns designed to increase share-of-wallet, reduce churn, drive retention, and improve loyalty. Oversee evaluation of the impact of product investments on ROI, including impact on revenue, unit economics, and overall consumer and merchant experience. Qualifications: Graduate degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, electrical engineering, mathematics, physics) with 10+ years of related professional experience (or PhD with 8+ years). 10+ years of experience managing AI and / or ML teams, working collaboratively with engineering and cross-functional partners, and / or guiding data-influenced product planning, prioritization, and strategy development. Demonstrated experience in hiring, retaining, and scaling diverse, geographically dispersed, high-performing teams. Expertise in ML with hands-on experience in building and implementing large-scale predictive models. Familiarity with ML modelling techniques (e.g., deep learning, gradient boosting, graph, NLP/LLM, regression, clustering etc.).
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