Staff Fraud Risk Analyst, Credit Karma

Job description

Intuit’s Trust and Safety team harnesses the power of data, technology, and people to protect our customers, partners, and business from fraud and abuse. The team is looking for a Staff Fraud Risk Analyst who is passionate about data and excited to partner with product managers, engineers, and data scientists to deliver fresh insights and intelligent solutions to fight fraud. This individual will build a deep understanding of Credit Karma’s perimeter (registration, login, and account recovery) and Marketplace, and apply industry best practices and cutting-edge AI to solve large-scale fraud challenges like identity theft, account takeover, fake account creation, and Marketplace abuse.

Responsibilities

Lead multi-quarter initiatives to understand fraudulent behavior across the Credit Karma perimeter and Marketplace, identify risk trends in the data, and turn them into policy and product recommendations. Become a subject matter expert for Credit Karma perimeter and Marketplace fraud, and own the fraud and risk case for launches, experiments, and roadmap tradeoffs. Make fast, well-reasoned calls on high-risk cases, and own the outcome through resolution, including post-incident learnings.

Partner with product, engineering, data science, and investigations to build intelligent, scalable controls that balance fraud loss against member experience. Identify gaps in metrics and data, and own scalable fixes. Define and track KPIs such as fraud rate, precision and recall, customer insult rate, and ATO and fake-account rates. Build dashboards that show the impact of fraud and of the policies meant to stop it. Use AI and GenAI tools to speed up analysis, find new fraud patterns, and automate manual fraud workflows.

Advocate for curated, standardized, centralized fraud datasets for Intuit-wide analysis. Use SQL, Python, Databricks, Tableau, and spreadsheets to analyze large datasets and guide policy decisions. Document and explain complex analyses and processes to leadership, and build alignment across technical and non-technical teams. Mentor and coach analysts, and raise the team's technical and analytical bar.

Qualifications

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 and risk in large datasets, and to use statistical analysis to justify policy recommendations. Experience in identity, authentication, or account-lifecycle fraud (ATO, account creation abuse, recovery abuse) and/or marketplace, lead, or partner fraud preferred.

Hands-on experience applying AI/GenAI to fraud detection or analytics workflows. Experience with fraud KPIs (precision, recall, chargeback, customer insult rate) and with data visualization tools (Tableau, Looker, Excel, GSheets). Decisive judgment and ownership of outcomes in fast-moving cases, with a fraud and risk mindset and deep familiarity with the product surface being protected. Outstanding communication and influencing skills, with a record of driving decisions across org boundaries.

Detail-oriented, proactive, accountable, team player, and empathetic. Bachelor's degree in a quantitative field or equivalent experience; Master's degree preferred. 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: San Diego $163,000 - $221,000