Staff Fraud Risk Analyst

Intuit

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Quick summary

Work type: On-site
Location: Mountain View, CA
Salary: $176,500–$238,500 / yr
Posted: 9 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $174k

This role $208k

$119k most similar roles pay here $251k

This role pays more than 71% of similar roles. Most pay $131,385–$216,525 — the shaded band above. At the midpoint, this role pays about $208k versus about $174k for comparable roles.

Based on 239 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 174 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 152 roles with salary data.

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At a glance

TL;DR · Staff Fraud Risk Analyst

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As a Staff Fraud Risk Analyst - Fintech on the Fraud Risk Management team, you will develop, optimize, and manage strategies for fraud risk management throughout the product lifecycle of Intuit’s Business Credit Card. You will identify emerging trends like identity fraud, bust out, check kiting, account take over, and transaction fraud while building adaptive defenses to minimize losses. Collaborating with Data Science and credit risk teams, you will develop prediction models, monitoring metrics, and performance dashboards. Your work involves evaluating tools for underwriting and exposure management while leveraging AI and automation to improve detection precision. You will utilize SQL, SAS, Python, R, and Tableau to perform quantitative analysis on hit rates and false positive rates. This role focuses on balancing fraud prevention with a seamless customer experience within the business credit card product area.

Skills

SQL Python R SAS Tableau Machine Learning AI Automation Regression Modeling Fraud Risk Management Data Science Analytics

What you'll do

Develop and refine fraud risk management strategies for underwriting, transaction monitoring, and exposure management.
Identify emerging fraud trends using data-driven and machine learning-enabled approaches.
Perform quantitative analysis on hit rates, false positives, and cost-benefit analyses to evaluate fraud defenses.
Partner with Data Science teams to identify modeling needs and enhance fraud model performance.
Create fraud monitoring metrics, early warning indicators, and performance dashboards for stakeholders.
Evaluate and manage external fraud tools, vendors, and partnerships to ensure advanced capabilities.
Utilize AI and automation to improve the speed, scalability, and precision of fraud detection.

What we're looking for

Bachelor’s degree in Business, Finance, Economics, Mathematics, Engineering, or another quantitative discipline.
Minimum of 6 years of experience in fraud risk analytics and risk management.
Familiarity with risk scoring and modeling techniques including regression modeling, multivariate analyses, and machine learning.
Proven expertise with industry-standard tools, fraud platforms, and best-in-class risk models.
Proficiency with analytical packages and tools such as SQL, SAS, Python, R, and Tableau.
Excellent analytical and problem-solving skills to convert insights into business recommendations.
Exceptional verbal and written communication skills to communicate complex ideas and influence decision making.

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