Senior Data Scientist

PayPal

Hybrid

Quick summary

Work type
Hybrid
Location
Chicago, IL
Salary
$153,317–$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 $187k
$88k most similar roles pay here $236k

This role pays more than 75% of similar roles. Most pay $126,800–$184,900 — the shaded band above. At the midpoint, this role pays about $187k 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

Senior Data Scientist position available in Chicago, IL for a role within PayPal’s risk management team. This senior-level role involves leading the development and implementation of advanced data science models to combat fraud and abuse by leveraging Python, SQL, and BigQuery. Day-to-day responsibilities include designing decision models, integrating prediction models into systems, optimizing risk frictions, and ensuring data integrity through collaboration with cross-functional teams. Candidates must have expertise in applying machine learning algorithms for financial data analysis, developing regression-based default models, and building scalable data pipelines using Python and cloud tools. The role requires extensive experience in deploying analytical models to production environments and communicating findings to stakeholders. This position addresses critical business challenges in the fraud detection space at a large scale, ensuring PayPal’s customers remain safe while maintaining operational efficiency.

What you'll do

  • Lead the development and implementation of advanced data science models for fraud detection.
  • Design and implement risk decision models using Python, SQL, and BigQuery.
  • Optimize risk frictions to maintain loss within targets while ensuring customer safety.
  • Validate underlying data and address critical data challenges with engineering teams.
  • Guide junior data scientists in delivering projects and bridging knowledge gaps.

What we're looking for

  • Master’s degree in Computer Science, Engineering, or related field plus 2 years of experience.
  • Apply machine learning algorithms for fraud detection using supervised and unsupervised methods.
  • Develop and validate regression-based default models for fraud prediction.
  • Conduct large-scale data analysis using SQL/SAS/Python.
  • Build scalable data pipelines using Python, SQL, and cloud tools.
  • Deploy analytical or ML models into production environments on cloud platforms.
  • Communicate model insights and fraud trends to cross-functional teams.

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