Manager, Data Analytics

PayPal•San Jose, CA

44d•$94,000 - $156,200•Hybrid

About The Position

We are seeking a data-driven Product Analytics Professional to join our team and drive product decisions through deep analytical insights. This role will be instrumental in understanding user behavior, measuring product performance, and identifying opportunities for growth and optimization. The ideal candidate will bridge the gap between complex data and actionable business insights.

Requirements

5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.
Advanced proficiency in SQL for data extraction and manipulation
Experience with analytics platforms (Google Analytics, Mixpanel, Amplitude, or similar)
Proficiency in data visualization tools (Tableau, Looker, Power BI, or similar)
Strong statistical analysis skills and experience with A/B testing methodologies
Programming experience in Python or R for data analysis
Strong problem-solving abilities with attention to detail
Experience designing and analyzing experiments
Ability to translate complex data into clear, actionable insights
Understanding of statistical concepts and their practical applications
Experience with predictive modeling and forecasting techniques
Excellent written and verbal communication skills
Ability to present complex findings to both technical and non-technical audiences
Strong storytelling abilities using data and visualizations
Experience facilitating cross-functional discussions and workshops
Understanding of product development lifecycle and methodologies
Knowledge of key business metrics and their relationships
Ability to connect analytical insights to business impact
Experience working in agile development environments
Intellectual curiosity and passion for uncovering insights from data
Strong collaboration skills and ability to work effectively in cross-functional teams
Self-motivated with ability to manage multiple projects simultaneously
Adaptability to work in a fast-paced, evolving environment
Detail-oriented with commitment to data accuracy and quality

Nice To Haves

Bachelor's degree or Master's in Analytics, Statistics, Mathematics, Economics, Computer Science, or related field
3-5 years of experience in product analytics, business intelligence, or data science
Proven track record of using data to drive product decisions and business outcomes
Knowledge of machine learning techniques and their applications
Familiarity with data warehousing concepts and ETL processes
Experience with customer segmentation and personalization strategies
Background in user experience research or behavioral psychology
Certification in relevant analytics platforms or tools

Responsibilities

Manage, coach, and develop a team of data analysts.
Oversee day-to-day delivery of analytics projects and reporting.
Ensure accuracy, consistency, and quality of all team outputs.
Collaborate with business units to prioritize analytics initiatives.
Communicate insights and recommendations to mid-level leadership.
Analyze user behavior, product usage patterns, and customer journey data to identify trends and opportunities
Design and implement measurement frameworks for product features and initiatives
Create comprehensive dashboards and reports to track key product metrics and KPIs
Conduct A/B tests and experiments to validate product hypotheses and measure impact
Perform cohort analysis, funnel analysis, and retention studies to understand user engagement
Partner with product managers, engineers, and designers to define success metrics for new features
Provide data-driven recommendations to inform product roadmap and prioritization decisions
Present findings and insights to stakeholders across all organizational levels
Identify opportunities for product improvements based on data analysis
Support go-to-market strategies with user segmentation and targeting insights
Build and maintain automated reporting systems and data pipelines
Ensure data quality and accuracy across product analytics platforms
Collaborate with engineering teams to implement proper event tracking and data collection
Develop statistical models to predict user behavior and product performance
Create self-service analytics tools for cross-functional teams
Measuring and optimizing user onboarding and activation flows
Analyzing feature adoption and usage patterns across different user segments
Supporting product experimentation through rigorous A/B testing programs
Building predictive models for user retention and lifetime value
Creating executive-level reporting on product performance and growth metrics
Collaborating on data strategy and infrastructure improvements