Senior Data Scientist
About The Position
PayPal, Inc. is seeking a Senior Data Scientist in San Jose, California. This role leads the development and implementation of advanced data science models and algorithms, works with stakeholders to understand requirements and deliver solutions, drives data science best practices, ensures data quality, and mentors junior scientists. The position focuses on measuring and improving PayPal’s Agentic Commerce offering across LLM platforms. The scientist will design controlled experiments, apply causal inference to assess product effects on revenue and conversion, model merchant and consumer behavior in conversational commerce, and build frameworks to measure growth, conversion, latency, availability, and friction. The role collaborates with Product and Engineering teams to optimize the experience using data-driven insights. Partial telecommuting is permitted from within a commutable distance of San Jose. The position is 40 hours per week, Monday through Friday, 9:00 a.m. to 5:00 p.m., with no travel expected. The role requires legal authorization to work in the United States without sponsorship.
Requirements
- Master’s degree, or foreign equivalent, in Computer Science, Engineering, Data Science, Statistics, or a closely related field.
- At least two years of experience in the job offered or a related occupation.
- At least two years of experience using Python and SQL for data analysis, querying databases, and machine learning.
- At least two years of experience with statistical analysis, probability, hypothesis testing, parametric and non-parametric tests, A/B testing frameworks, and product analytics.
- At least two years of experience with Bayesian statistics and mixed effect modeling to measure product launches.
- At least two years of experience with machine learning and predictive modeling, including scikit-learn, TensorFlow, or PyTorch for building and deploying models.
- At least two years of experience with data visualization tools, including Tableau, Looker, Plotly, Dash, and Matplotlib/Seaborn, for presenting insights.
- At least two years of experience with ETL pipelines and data warehouses to work with structured and unstructured data.
- At least two years of experience translating data insights into actionable business strategies and communicating findings to stakeholders.
- At least two years of experience with AWS, GCP, or Azure for cloud computing, storage, and model deployment.
- At least one year of experience working with PySpark and Hadoop for handling large-scale datasets.
- At least one year of experience with probability modeling using Monte Carlo simulation and related stochastic techniques.
- Must be legally authorized to work in the United States without sponsorship.
Responsibilities
- Design and execute controlled experiments to measure the effectiveness of PayPal's Agentic Commerce offering across LLM platforms.
- Apply causal inference methodologies to attribute revenue and conversion changes to product features in AI-driven checkout flows.
- Develop behavioral models to understand merchant and consumer interactions within conversational commerce environments.
- Build measurement frameworks to track key performance metrics across growth, conversion, latency, availability, and friction for emerging AI commerce channels.
- Collaborate with Product and Engineering teams to optimize the Agentic Commerce experience based on data-driven insights.
- Lead the development and implementation of advanced data science models and algorithms.
- Work with stakeholders to understand requirements and deliver solutions.
- Drive data science best practices and ensure data quality.
- Mentor junior scientists.
Benefits
- Comprehensive, choice-based programs supporting physical, emotional, and financial wellbeing.
- Generous paid time off.
- Healthcare coverage for the employee and family.
- Resources to support financial security and mental health.
- Additional compensation may include an annual performance bonus, equity, or other incentive compensation, as applicable.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
