Payments Risk Analyst Jobs in California (NOW HIRING)

• Serve as the primary risk analytics partner across QuickBooks Payments, Payroll, Bill Pay, and Capital — delivering cross-product insights that no single product team could surface alone.
• Build and maintain automated risk dashboards covering transaction approval rates, fraud losses, payroll disbursement anomalies, bill pay failure rates, and Capital portfolio health — with AI-generated narrative summaries for leadership.
• Develop reusable frameworks for policy impact sizing so that rule changes in Payments fraud, Payroll verification, Bill Pay limits, or Capital underwriting come to committee pre-quantified.
• Design and execute champion/challenger experiments across products (e.g., testing new authentication flows in Payments, alternative verification steps in Payroll, adjusted credit limits in Capital).
• Build loss forecasting and early warning systems tailored to each product's risk dynamics — real-time signals for Payments/Bill Pay, vintage-based models for Capital, disbursement pattern detection for Payroll.
• Optimize approval and intervention strategies through simulation and segmentation — reducing false declines in Payments, minimizing payroll holds for legitimate businesses, and right-sizing Capital offers.
• Enable self-serve analytics across product and ops teams by deploying AI-assisted query tools, so Tier-1 questions about QuickBooks risk metrics don't require analyst time.
• Ensure responsible AI usage by building internal playbooks for how AI-generated insights are applied in risk decisions across the QuickBooks ecosystem.
• Deliver executive strategy briefs that connect risk performance across all four products, positioning the Risk team as a growth enabler — not just a control function.

Decision Optimization Across the Lifecycle

• Payments: Approval Strategy Optimization — ML-driven simulation of fraud rule thresholds; swap-set analysis quantifying revenue lift from reducing false declines while holding loss rates flat.
• Payroll: Disbursement Risk Scoring — Develop risk-tiered verification flows — streamlining onboarding for trusted businesses while adding friction only where exposure warrants it.
• Bill Pay: Authorization & Limit Optimization — Analyze payment failure patterns and unauthorized attempt clusters to refine per-customer limits and authentication triggers.
• Capital: Underwriting & Portfolio Strategy — Segmentation-driven offer optimization — right-sizing loan amounts and pricing based on QuickBooks behavioral data (revenue trends, payment history, payroll consistency).

Scalable Frameworks & Organizational Leverage

• Cross-Product Champion/Challenger Platform — Standardized test-and-learn methodology that Payments, Payroll, Bill Pay, and Capital teams all use — with AI-powered monitoring and automated executive readouts of experiment results.Loss 
• Forecasting & Early Warning — Product-specific leading indicators (real-time velocity for Payments, payroll run anomalies for Payroll, vintage curves for Capital) unified into a single early warning view.
• Self-Serve Analytics for QuickBooks Risk — AI chatbot layer on curated data so product managers and ops leads can answer "what's my approval rate for segment X this week" without filing a ticket.

Strategic Influence & Enterprise Scale

• New Product/Feature Risk Assessment — LLM-assisted scenario generation for pre-launch risk sizing — e.g., launching instant payouts in Payments, expanding Capital to new segments, adding recurring Bill Pay features.
• Model Monitoring Automation — Continuous compliance pipelines with AI-flagged drift detection across all production models spanning the four product lines.
• AI Governance & Responsible Use Playbook — Auditable, explainable AI usage standards for risk decisions across the QuickBooks ecosystem.
• Executive Strategy Briefs — Quarterly "state of QuickBooks risk" narratives connecting performance across Payments, Payroll, Bill Pay, and Capital to inform enterprise strategy.

• 10+ years of experience in analytics, data science, or quantitative risk roles within financial services or fintech.
• Strong business acumen with demonstrated ability to translate analysis into strategic recommendations for senior leadership across multiple product lines.
• Expert SQL and Python/R skills; experience building automated reporting and analytical pipelines at scale.
• Experience supporting multiple business lines or products simultaneously — comfortable context-switching between payments, lending, and operational risk domains.
• Familiarity with AI/ML tools (LLMs, copilots, predictive modeling) and a track record of applying them to accelerate analytical output.
• Excellent communication skills — ability to present complex findings clearly to product leaders, engineers, and executives.
• Understanding of the small business financial ecosystem and how products like Payments, Payroll, Bill Pay, and Capital interconnect.

Preferred

• Experience in payment fraud, ACH/RTP risk, payroll disbursement controls, or SMB lending/credit risk.
• Background in experimentation design (A/B testing, champion/challenger frameworks) in a product-driven environment.
• Experience with BI tools (Tableau, Looker, Power BI) and cloud data platforms (Databricks, Snowflake, AWS/GCP).
• Familiarity with regulatory requirements relevant to payments, lending, and payroll (BSA/AML, fair lending, NACHA rules).
• Prior experience at Intuit, QuickBooks, or a comparable SMB fintech platform.
• Graduate degree in a quantitative field (Statistics, Economics, Data Science, Engineering, or related).