Chime Financial, Inc - Insights Analyst, Dispute Experience
Requirements
• 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.Ability to drive alignment and decision-making across teams. • Mindset of strong ownership and urgency, proactive communication, and a bias toward action and clarity. • #LI-MM1 #LI-Remote
Responsibilities
• 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.
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