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: 21 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 fraud risk strategies throughout the product lifecycle for Intuit’s Business Credit Card. You will focus on identifying and mitigating risks such as identity fraud, bust out, check kiting, account take over, and transaction fraud while balancing customer experience with program profitability. Your daily work involves partnering with Data Science teams to build prediction models and performing quantitative analyses of hit rates and false positive rates. You will also evaluate external tools and leverage AI and automation for detection speed. Required skills include proficiency in SQL, SAS, Python, R, and Tableau, along with expertise in regression modeling, multivariate analysis, and machine learning to address complex fraud patterns within the business credit card product area.

Skills

SQL Python R SAS Tableau Machine Learning AI Automation Regression Modeling Fraud Risk Management Risk Scoring

What you'll do

Develop and refine fraud risk management strategies for underwriting, transaction monitoring, and exposure management.
Use data-driven and machine learning approaches to identify emerging fraud trends and build defenses.
Perform quantitative analysis on hit rates, false positives, and cost-benefit analyses to evaluate fraud tools.
Partner with Data Science teams to identify modeling needs and improve fraud model performance.
Create fraud monitoring metrics and early warning indicators reported through performance dashboards.
Evaluate and manage external fraud tools, vendors, and partnerships for the product.
Leverage AI and automation to increase 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 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 for fraud prevention.
Proven expertise with industry-standard tools, fraud platforms, and best-in-class risk models.
Excellent analytical and problem-solving skills to convert analysis insights into business recommendations.
Exceptional verbal and written communication skills to communicate complex ideas and influence decision making.
Proficiency with analytical packages and tools such as SQL, SAS, Python, R, and Tableau.

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