Staff Fraud Risk Analyst - Fintech
Intuit
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Mountain View, CA · Posted August 19, 2026
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November 2026
- #1Best cities for AI-skill jobs45% · of 100
- #1Best cities for AI-skill jobs in the West Coast45% · of 71
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- #2Best cities for finance pay after cost of living$161k · of 35
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Among financial specialists, all other, AI is already used for some of the tasks. Measured exposure for financial specialists, all other: 22% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Intuit has filed one layoff notice in the last twelve months, covering 162 workers, most recently May 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings
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About the job
One out of every two small businesses fails within their first five years, most often due to running out of cash. QuickBooks Capital is on a mission to make a dent in that statistic, by providing small businesses access to the capital they need when they need it, leveraging the data inside QuickBooks for faster and better decisioning. This way, our customers never again have to worry about not making payroll or saying no to a business opportunity. That’s how we power prosperity.
Intuit's Business Credit Card, a Quickbooks Capital product, is one of the company's most exciting new product launches, with aggressive growth plans and significant customer demand on the horizon. We are looking for top talent and team members that love new challenges, cracking tough problems and working cross-functionally. If you are looking to join a fast-paced, innovative and incredibly fun team, then we encourage you to apply.
As a key analyst of the Fraud Risk Management team for Intuit’s Business Credit Card, you will be responsible for developing, optimizing and managing strategies for fraud risk management through the product life cycle. You will be deeply familiar with typical fraud behaviors involving identity fraud, bust out, check kiting, account take over and transaction fraud, and will develop adaptive strategies to prevent and minimize fraud losses. You will partner heavily with the Data Sciences team in developing fraud risk prediction models, fraud pattern identification analyses and in devising the overall fraud risk mitigation strategy. You will also partner with the credit risk team in developing holistic approaches to mitigating total losses and setting program performance expectations. You will strive towards striking the optimal balance between great customer experience, program profitability and fraud risk mitigation.
You will be continually evaluating and onboarding new products and tools for fraud underwriting and exposure management and will actively partner with stakeholders across lending products to develop a coordinated strategy for external vendor usage. You will be an active proponent of leveraging AI and automation in developing analytical insights, updating models and deploying strategy changes.
Responsibilities
Develop, implement, and continuously refine fraud risk management strategies across credit card underwriting, transaction monitoring, and exposure management
Leverage data driven and machine learning-enabled approaches to devise fraud defenses and rapidly identify emerging fraud trends in the program
Continually evaluate fraud defenses through quantitative analysis of hit rates, false positive rates, A/B test results and cost-benefit financial analyses
Partner with the Data Science team to identify modeling needs and enhance fraud model performance
Develop fraud monitoring metrics, early warning indicators, trend analyses and report them through performance dashboards to various stakeholders
Drive cross-functional collaboration with Product, Engineering, Compliance, Marketing, and Operations to balance fraud prevention with seamless customer experience
Evaluate, onboard, and manage external fraud tools, vendors, and partnerships to ensure state-of-the-art capabilities
Leverage AI and automation to improve fraud detection speed, scalability, and precision
Qualifications
Bachelor’s degree in Business, Finance, Economics, Mathematics, Engineering or other quantitative disciplines
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, and their application in fraud prevention
Proven expertise with industry-standard tools, fraud platforms, and best-in-class risk models
Excellent analytical and problem-solving skills with a proven track record of converting analysis insights into business recommendations
Exceptional verbal and written communication skills to effectively communicate complex ideas and influence audiences in decision making
Proficiency with analytical packages and tools such as SQL, SAS, Python, R and Tableau
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Mountain View $176,500 - $238,500