Senior Data Scientist

PayPal

Hybrid

Quick summary

Work type: Hybrid
Location: Chicago, IL
Salary: $142,210–$221,500 / yr
Posted: 2 days ago
Closes: Jun 18, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $156k

This role $182k

$88k most similar roles pay here $236k

This role pays more than 74% of similar roles. Most pay $126,800–$185,527 — the shaded band above. At the midpoint, this role pays about $182k versus about $156k for comparable roles.

Based on 240 similar postings.

Employer

About PayPal

PayPal is a leading global digital wallet and online payment system, founded in 1998, that allows individuals and businesses to send, receive, and manage funds securely in over 200 markets.

PayPal currently has 84 open roles on FindRole.

Listed pay typically runs $160,500–$235,826 across 84 roles with salary data.

Most-posted roles

View all roles at PayPal

At a glance

TL;DR · Senior Data Scientist

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As a Senior Data Scientist at PayPal in Chicago, you will lead the development and implementation of advanced data science models and algorithms to drive product decision-making. Your day-to-day responsibilities include conducting deep-dive analyses such as causal inference analysis and A/B testing, identifying new opportunities through data analytics, and mentoring junior team members. You will work with stakeholders to resolve complex data challenges and ensure continuous improvement in KPIs. The role requires expertise in machine learning algorithms like Random Forest and XGBoost, PySpark/Spark for data manipulation, and Python for building automated pipelines on AWS and Snowflake. Additionally, you will develop dashboards using Tableau and maintain documentation in production environments. This position involves applying Scrum and Agile methodologies to manage projects effectively and communicate findings to various stakeholders.

Skills

Python SQL SAS PySpark Spark AWS Snowflake Tableau XGBoost Random Forest Scrum Agile CI/CD

What you'll do

Lead development and implementation of advanced data science models and algorithms.
Conduct deep-dive analyses including causal inference analysis and A/B testing.
Identify new business opportunities through data analytics and continuous improvement.
Mentor junior data scientists to ensure data quality and integrity standards.
Develop automated pipelines for SQL scripts on AWS and Snowflake environments.

What we're looking for

Master’s degree in Data Science, Business Analytics, or related field plus 2 years of experience.
Apply machine learning algorithms (Random Forest, XGBoost) to financial data for business insights.
Develop and recalibrate regression-based default models for financial portfolios.
Conduct large-scale data analysis using SQL/SAS on databases/servers.
Manipulate complex data structures with PySpark/Spark for data transformation.
Build automated pipelines in Python on AWS and Snowflake for cloud environments.
Deploy automated dashboards and benchmarks for risk monitoring using Tableau.

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