Intuit Staff Fraud Risk Strategy Analyst 

United States, California, Mountain View 

456378236

Fraud Detection & Investigation

• Monitor alerts and analyze real-time signals to detect suspicious activity (e.g., account takeover, check kiting, synthetic identity, mule activity, ACH fraud, remote access tools).

• Investigate and resolve fraud cases across onboarding, KYC, account funding (e.g., ACH, Plaid, RTP), and account usage stages.

• Leverage fraud tools and external vendor data to review high-risk activity and recommend actions. Data-Driven Analysis
• Analyze fraud trends and patterns using data analytics tools (SQL, Excel, dashboards) to identify emerging threats or gaps in current detection logic.

• Support creation and tuning of fraud detection rules, machine learning models, and velocity checks in collaboration with fraud strategy and data teams.

• Track key fraud KPIs (e.g., fraud loss rates, false positive rates, return reasons like R05/R10) and prepare reports for stakeholders. Operational Efficiency & Documentation
• Respond to fraud-related escalations from customer support and other internal teams.

• Assist in refining workflows and automations to improve response time and operational throughput.

• Document fraud scenarios, case investigations, root cause analysis, and preventive actions.

Cross-Functional Collaboration

• Work closely with compliance, risk policy, customer support, engineering, and external vendors.

• Participate in projects related to new product launches, fraud tooling enhancements, and regulatory reviews (e.g., SAR filings support).

• Provide fraud subject matter expertise in discussions related to account security, identity verification, and payment flows.

Bay Area California $172,000- $232,500

• 5–7 years of experience in fraud operations or fraud analytics, preferably in fintech, banking
• Bachelor's degree in quantitative fields such as Statistics, Mathematics, Finance, Data Science; or MS/PhD with 2+ years of relevant working experience
• Strong understanding of fraud typologies relevant to consumer financial products (e.g., synthetic identity, phishing/ATO, 1st/3rd party fraud, ACH disputes).
• Experience with fraud tools and platforms (e.g., Alloy, Sift, Ekata, Kount, etc.)
• Proficiency in analyzing fraud data using SQL and/or Excel; familiarity with Looker or other BI tools is a plus.
• Familiarity with banking regulations and fraud return codes (e.g., ACH NACHA rules, Reg E, KYC/AML basics).
• Strong analytical, investigative, and problem-solving skills.
• Excellent communication and documentation skills.

Nice to Have

• Experience in fraud for digital banking, challenger banks, or fintech products.
• Exposure to fraud rules management or machine learning-based detection systems.
• Prior work with ACH return reason codes, dispute handling, or chargeback processes.