PayPal Dir Product Management - Analytics 

United States, California, San Jose 

344546953

Job Responsibilities

• Lead and develop a high-performing team of data scientists, analysts, andproduct managersto build precise, scalable data models that drive actionable insights,building a metrics-driven culture across the organization.

• Partner with Product, Engineering, Design, and Operations teams to develop data models, predictive analytics, and machine learning-driven solutions that enhance user experiences and business outcomes.

• Develop analytics for financialengagement-based products,

• Design and build scalable data platforms, including data ingestion, monitoring, intelligence, and cataloging to support advanced analytics and machine learning workflows.

• Build andmachine learning feature pipelines to enhance model performance and real-time decision-making across products.

• Define and implement best practices for advanced analytics, A/B testing, and causation-based modeling to enhance data-driven decision-making.

• Develop and execute customer journey analytics,

• Partner with business leaders across Product,to define strategic priorities and influence key investments.

• Deliver high-impact analytics projects, uncovering new growth opportunities and improving customer experience.

, evaluate, and integrate new data sources to strengthen analytical capabilities and predictive modeling.

• Apply machine learning, predictive modeling, and deep learning algorithms to extract insights and optimize business performance.

• Ensure data infrastructure, governance, and quality align with best practices for enterprise-scale analytics.

• Communicate data-driven insights and recommendations to executive stakeholders, translating complex analyses into actionable strategies.

Requirements

• 10+ years of experience in Advanced Analytics, Data Science, or Machine Learning, with a focus on product analytics.

• Proven leadership experience managing high-performing teams of data scientists, data analysts, and data engineers.

• Hands-on experience in machine learning feature engineering, model development, and deployment.

• Strong background in SQL, Python, R, and ML frameworks (TensorFlow,, Scikit-Learn, etc.).

• Experience in data platform architecture, including data ingestion, monitoring, intelligence, and cataloging.

• Deep understanding of A/B testing, experimental design, and statistical modeling for decision-making.

• Experience with BI tools (Tableau, Looker, Amplitude, etc.) and enterprise data visualization best practices.

• Strong ability to translate complex data insights into strategic recommendations for product and business teams.

• Master’s degree preferred in Data Science, Computer Science, Statistics, Economics, or a related field.