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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Analyst, Data Analytics - **Company:** PayPal - **Location:** Austin, TX, United States (Remote available) - **Experience:** Expert - **Salary:** $148,741.0 - $193,600.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Business Analytics Applications, Data Analysis, Big Data, BigQuery, Business Systems, Databases, Information Engineering, Extract Transform Load (ETL), Data Mining, Data Structures, Relational Databases, Statistical Hypothesis Testing, Python (Programming Language), SQL Databases, Tableau (Software), Unstructured Data, Usage Analysis, Jupyter Notebook, Scripting, Data Strategy, Data Analytics, Data Pipelines - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=19b15f5b9370e17d ## About the Role Minimum Requirements: Bachelor's degree, or foreign equivalent, in Management Information Systems, Data Science/Analytics, or a closely related field plus seven years of experience in the job offered or a related occupation Special Skill Requirements: 1. SQL (Structured Query Language) - Data extraction, transformation, and analysis from large-scale relational databases preferably Big Query (7 years). 2. Jupyter Notebooks - Data analysis, experimentation, and automation (5 years). 3. Business Intelligence & Reporting - Designing KPI-driven reports and dashboards for decision-making, preferably Tableau (5 years). 4. Data Strategy & Gap Analysis - Identifying business inefficiencies, building solutions and developing scalable data-driven strategies (5 years). 5. Presentation & Storytelling with Data - Identifying the anomalies and translating complex analysis into actionable insights for stakeholders (3 years). 6. Product Analytics & Cross-Functional Collaboration - Partnering with product, engineering, and data science teams to define key product metrics, evaluate feature performance, and translate insights into product strategy decisions that enhance customer experience and business outcomes (3 years). 7. Statistical Analysis - Applying statistical techniques to identify trends, correlation, statistical tests and their inferences (2 years). 8. ETL & Data Pipeline Management - Working with structured/unstructured data flows across business systems (2 years). 9. Customer Experience Analytics & Journey Optimization - Analyzing customer experience data to identify pain points, optimize user journeys, and improve satisfaction and retention across servicing and product channels (2 years). 10. KPI Design & Business Metrics Development - Defining, validating, and standardizing key performance indicators that measure operational efficiency, customer experience, and product success (2 years). 11. A/B Testing & Experimentation - Designing, implementing, Hypothesis Testing and analyzing controlled experiments (1 year). Additional Responsibilities & Preferred Qualifications: EOE, including disability/vets. The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is ## Description Job Duties: Lead in gathering requirements, analyzing data, and programming data models to develop impactful reports, dashboards, and visualizations to drive PayPal's service experience strategy. Conduct rigorous data analyses on user experience reports to drive meaningful financial benefits for PayPal using SQL and scripting languages (like Python/R) with a deep understanding of structured and unstructured databases. Perform deep dive analytics including causal inference analysis, pre & post analysis, sensitivity analysis, financial projections, and other ad-hoc analyses on PayPal's product and customer experience data to identify and address customer pain points. Synthesize large volumes of data and develop data models to enable the development of key business metrics. Clean, manipulate, and merge data from diverse datasets to enable the creation of compelling data stories. Collaborate with product engineering and data engineering to enable feature tracking, resolve complex data and tracking issues, and build necessary data pipelines. Partner with data engineers, product engineers, and data scientists to build robust data structures and streamline multi-system processes. Work with analytics teams during rigorous exploratory data analyses to guide customer experience strategy, analyze business performance and health, triage issues, and create executive-friendly info-insight packets. Partner closely with product leaders to understand new product offerings being built and recommend the right metrics to measure the performance of those features. Perform and evaluate complex experiments (A/B Testing) and related concepts. Utilize data-driven insights to brainstorm and refine engagement strategies, ensuring a measurable impact on incremental engagement and revenue. Define, track, and refine KPI frameworks to evaluate servicing experience and product performance, and cultivate best practices in analytics instrumentation and experimentation. Design and develop high-quality dashboards and analytical tools using Tableau and conduct reproducible analyses in Jupyter Notebooks. Develop domain expertise in Servicing and Customer Experience to inform analysis and recommendations. Manage and deliver multiple analytics projects concurrently in a fast-paced, results-oriented environment. 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