Staff Fraud Risk Analyst

Intuit

Confirmed live today High trust

Quick summary

Work type
On-site
Location
San Diego, CAMountain View, CA
Salary
$163,000–$221,000 / yr
Posted
5 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $179k
This role $192k
$124k $234k
below market most similar roles pay here above market

This role pays more than 58% of similar roles. Most pay $135,000–$223,075 — the blue band above. At the midpoint, this role pays about $192k versus about $179k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 256 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 237 roles with salary data.

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At a glance

TL;DR · Staff Fraud Risk Analyst

The Staff Fraud Risk Analyst joins the Trust and Safety team to protect Credit Karma from fraud and abuse. This role involves leading multi-quarter initiatives to identify risk trends across the registration, login, account recovery, and Marketplace perimeters. The analyst will build intelligent, scalable controls to combat identity theft, account takeover, and fake account creation while balancing fraud loss against member experience. Key responsibilities include owning fraud cases for product launches, defining KPIs like precision and recall, and automating workflows using AI and GenAI tools. The candidate must use SQL, Python, Databricks, Tableau, and spreadsheets to analyze large datasets and provide policy recommendations. This position requires deep domain expertise in identity, authentication, and marketplace fraud to solve complex, large-scale security challenges.

What you'll do

  • Lead multi-quarter initiatives to identify fraud trends and convert them into policy and product recommendations.
  • Own the fraud and risk case for new product launches, experiments, and roadmap tradeoffs.
  • Make fast, well-reasoned decisions on high-risk cases and manage the resolution and post-incident learnings.
  • Partner with technical teams to build scalable controls that balance fraud loss against member experience.
  • Define and track KPIs such as fraud rate, precision, recall, and customer insult rates using dashboards.
  • Use AI and GenAI tools to automate manual workflows and identify new fraud patterns.
  • Analyze large datasets using SQL, Python, and Databricks to guide policy decisions.
  • Mentor and coach analysts to raise the team's technical and analytical standards.

What we're looking for

  • 8+ years of relevant experience in fraud prevention, risk, or a similar analytical role with strong business acumen.
  • Advanced SQL and Python skills for profiling, segmentation, and aggregation on large datasets (BigQuery/Databricks preferred).
  • Proven ability to find fraud patterns in large datasets and use statistical analysis to justify policy recommendations.
  • Experience in identity, authentication, or account-lifecycle fraud and/or marketplace, lead, or partner fraud (preferred).
  • Hands-on experience applying AI/GenAI to fraud detection or analytics workflows.
  • Experience with fraud KPIs and data visualization tools like Tableau, Looker, Excel, or GSheets.
  • Outstanding communication and influencing skills with a record of driving decisions across organizational boundaries.
  • Bachelor's degree in a quantitative field or equivalent experience; Master's degree (preferred).

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