Insights Analyst, Dispute Experience

About the role

As an Insights Analyst supporting Chime's Trust & Safety Pillar at OMX, you will play a criticalx role in strengthening the integrity of our platform by delivering deep analytical insights across Dispute Operations, Fraud Operations, Product Management, Engineering, and Risk. Your work will directly influence how Chime protects members, drives operational efficiency and resilience, reduces losses, and prevents abuse. In this highly visible role, you will partner closely with Fraud Ops, Disputes Ops, Risk, Product, and Engineering teams to diagnose emerging risks, quantify operational impacts, and develop recommendations that improve decision accuracy, automation effectiveness, and operational performance. You will bring strong analytical rigor, exceptional communication skills, and the ability to translate complex data signals into clear, actionable insights for senior leaders. This role requires a strategic thinker who can proactively identify gaps, drive analytical frameworks, and ensure cross-functional alignment in a rapidly evolving Trust & Safety environment. The base salary offered for this role and level of experience will begin at $138,000.00 and up to $190,000.00 Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. In this role, you can expect to Analytics & Root-Cause Identification Translate complex data signals into root-cause narratives and actionable operational or product recommendations. Define success metrics, KPIs, monitoring frameworks, and develop predictive analytics mechanisms for Disputes and Fraud Ops. Build enhanced metric and KPI frameworks that help identify emerging trends, performance shifts, and anomalies across Fraud Ops and Dispute Ops. Conduct in-depth workflow and lifecycle analyses-such as examining interaction patterns, segment behaviors, and before/after performance changes-to identify friction points, root causes, and opportunities to improve Trust & Safety processes. AI-Enabled Automation & Decisioning Partner with Product, Engineering, Fraud Strategy, and Ops to evaluate and improve AI-enabled workflows, including automated decisioning, classification models, and agent augmentation tools. Analyze model outputs, false positives/negatives, and decision accuracy to recommend enhancements. Measure operational and member impact of automation changes and support the design of new AI features (e.g., routing logic, contact summarization, anomaly detection). Experimentation & Evaluation Design and evaluate A/B tests, policy changes, rule deployments, workflow adjustments, and operational interventions. Surface statistically robust insights to inform go/no-go decisions and rollout strategies. Develop sizing models that quantify the operational, financial, and member impact of proposed policy, workflow, or automation changes, providing clear forecasts that support data-driven rollout decisions. Executive Communication & Storytelling Create concise, executive-level summaries that distill investigations into clear narratives with quantified impacts and recommended next steps. Present Trust & Safety insights to senior leadership across Operations, Risk, Product, and Engineering. Cross-Functional Alignment & Leadership Work closely with Operations, Risk, Product, and Engineering to ensure shared understanding of problems and alignment on solutions. Proactively communicate progress, updates, timelines, and risks across stakeholders. Help drive clarity in ambiguous environments, especially during live issues and emerging operational events. To thrive in this role, you have Technical Skills Bachelor's degree in a quantitative field (Statistics, Data Science, Economics, Mathematics, Computer Science, Engineering). 5+ years in analytics, ideally in Trust & Safety, Fraud, Risk, or Support Operations. Advanced SQL skills (complex joins, window functions, CTEs). Proficiency in Python or R for experimentation, modeling, and data analysis. Strong understanding of statistics, causal inference, experiment design, and anomaly detection. Experience analyzing automation systems, risk models, or ML-driven workflows is a plus. Experience with BI tools such as Looker or Mode. Domain Expertise Experience in fintech, digital banking, payments, fraud, or Trust & Safety environments. Experience evaluating or supporting AI/ML systems, including monitoring false positives/negatives and model performance. Ability to break down ambiguous issues into structured analytical frameworks. Strong understanding of how product, operations, and engineering intersect in Trust & Safety domains. Communication & Leadership Outstanding written and verbal communication skills, especially in synthesizing complex topics for executives. Proven track record of taking end-to-end ownership of cross-functional initiatives.