VP, Product Data Science

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 Summary:

The Vice President (VP) of Product Data Science is a senior leadership position responsible for guiding the data science strategy within an organization, particularly in relation to product development and optimization. This role combines technical expertise in data science with strategic business acumen to drive data-driven decision-making and enhance product performance.

Job Description:

Key Responsibilities

Strategic Leadership

• Develop and implement data science strategies that align with the company's overall business goals.  

• Collaborate with other executives to identify opportunities for leveraging data to drive growth and efficiency.

Team Management

• Lead and mentor a team of data scientists and analysts, fostering a culture of innovation and continuous improvement.  

• Ensure the team is equipped with the necessary tools and training to succeed.

Data Governance and Compliance

• Oversee data governance policies to ensure compliance with regulations and best practices.  

• Implement data quality standards and practices to maintain the integrity of data used in decision-making.

Advanced Analytics and Insights

• Utilize advanced analytics techniques, including machine learning and predictive modeling, to extract actionable insights from data.  

• Present findings to stakeholders to inform product development and marketing strategies.

Cross-Functional Collaboration

• Work closely with product management, marketing, and operations teams to identify data-driven opportunities for product enhancements.  

• Facilitate communication between technical teams and non-technical stakeholders to ensure alignment on objectives.

Required Skills & Qualifications

• Educational Background: Typically requires a Master's or Ph.D. in Data Science, Statistics, Computer Science, or a related field.

• Experience: Significant experience in data science, analytics, or a related field, with a proven track record in a leadership role.

• Technical Skills: Proficiency in data analysis tools and programming languages (e.g., Python, R, SQL).

• Business Acumen: Strong understanding of business operations and the ability to translate data insights into strategic recommendations.

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