Sr Data Scientist, Fraud Risk Oversight

PayPal

Hybrid

Quick summary

Work type: Hybrid
Location: Austin, Texas · Chicago, Illinois
Salary: $130,500–$193,600 / yr
Posted: 63 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $158k

This role $162k

$97k most similar roles pay here $227k

This role pays more than 55% of similar roles. Most pay $126,800–$189,250 — the shaded band above. At the midpoint, this role pays about $162k versus about $158k 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 · Sr Data Scientist, Fraud Risk Oversight

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As a senior data scientist on the fraud prevention team at PayPal, you will lead the development and implementation of advanced data science models to combat emerging fraud patterns. Your day-to-day responsibilities include independently validating fraud strategies, conducting deep-dive analytics on transactional and identity data, and advising senior leadership on risk controls. You will leverage Python and SQL to extract insights from large datasets and use tools like Tableau or Seaborn for data visualization. This role requires a deep understanding of various fraud typologies such as account takeover and payment fraud, along with expertise in risk management frameworks.

Skills

Python SQL Tableau Looker Power BI Seaborn Plotly

What you'll do

Critically evaluate the effectiveness of fraud strategies developed by the First Line of Defense.
Perform deep-dive analytics to identify emerging fraud patterns and vulnerabilities in transactional data.
Provide domain expertise on various fraud typologies and risk management frameworks.
Act as a subject matter expert to advise senior leadership on proposed risk controls.
Use Python and SQL for extracting insights from large-scale datasets related to fraud detection.

What we're looking for

Advanced proficiency in Python and SQL for data analysis.
Deep understanding of fraud typologies and risk management frameworks.
Experience in performing deep-dive analytics on transactional and identity data.
Skilled in data visualization tools like Tableau or Python libraries (Seaborn, Plotly).
Ability to critically evaluate the effectiveness of fraud strategies independently.
Serve as a subject matter expert to advise senior leadership on risk controls.

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