Data Scientist 1 at PayPal

Compensation · Listed in posting

$174,304 – $243,500/yr

Setup: Hybrid
Location: San Jose, California
Type: Full-time
Level: entry
Posted: Sep 23, 2026

Description

PayPal is hiring a Data Scientist 1 in San Jose, California, to build predictive lead-scoring and other analytical models, deploy technical solutions, manage end-to-end analytics projects, and translate data insights into business recommendations. The role requires a master’s degree or equivalent in a relevant quantitative field and two years of experience, with extensive experience in Python, SQL, statistics, machine learning, causal inference, data visualization, large-scale data processing, cloud deployment, ETL, and stakeholder communication. The position offers partial telecommuting and a base salary of $174,304 to $243,500 per year.

Required Skills

Python
SQL
Machine learning
Statistical analysis
A/B testing
Causal inference
scikit-learn
Tableau
PySpark
AWS
ETL pipelines

Additional Information

Minimum Education: Master’s degree or foreign equivalent in Data Science, Quantitative Management, or a closely related field
Required Previous Experiences: Two years of experience in the offered job or a related occupation
Two years of experience using Python and SQL for data analysis, database querying, and machine learning
Two years of experience with statistical analysis, hypothesis testing, A/B testing, and product analytics
Two years of experience with Bayesian statistics and mixed-effect modeling for product launches
One year of experience with causal inference methods for measuring product impact
One year of experience with machine learning and predictive modeling using scikit-learn
Two years of experience with data visualization using Tableau, Looker, Plotly, Dash, Matplotlib, and Seaborn
Two years of experience handling large-scale datasets with PySpark, Hadoop, or BigQuery
Two years of experience with cloud computing, storage, and model deployment on AWS, GCP, or Azure
Two years of experience designing ETL pipelines and working with structured and unstructured data in data warehouses
Two years of experience translating data insights into business strategies and communicating findings to stakeholders