• Analyze real-time telemetry alerts and operational datasets to validate incidents, identify anomalies, and assess operational impact. • Differentiate true events from false positives, duplicate alerts, and known recurring conditions. • Correlate trends, timestamps, logs, and event data to support severity assessment and operational decision-making. • Prepare clear, data-backed incident summaries to support client and stakeholder response activities. • Provide analytical context and data-driven insights to clients and external vendors during incident investigations. • Track remediation actions, response timelines, and outcomes using structured operational data. • Support escalation and prioritization decisions through evidence-based analysis. Communicate findings clearly and concisely to operations, service management, and project stakeholders. • Identify recurring incident patterns, systemic operational risks, and vendor performance trends. • Highlight gaps in telemetry coverage, data quality, alert logic, or monitoring effectiveness. • Recommend opportunities for alert tuning, automation, and improved monitoring or reporting practices. • Support continuous improvement initiatives by surfacing actionable insights from operational data. • Maintain accurate, auditable records of analyses, incidents, and findings in approved client and company tools. • Contribute analytical insights to improve runbooks, alert definitions, and operational standards. • Support initiatives aimed at reducing Mean Time to Resolution (MTTR) and minimizing repeat incidents.

• Lead and mentor a team of analysts, ensuring they have the support and clarity needed to succeed in a fast-paced environment. • Understand funnels, ecosystems, user behaviors, and long-term trends in the adoption of our products to identify opportunities for step-changes of specific customer segments. • Develop and maintain comprehensive KPI trees and frameworks to provide clear visibility on domain performance and trends. • Define key metrics reflecting product success and monitor health, while identifying growth opportunities in retention, engagement, and monetization through quantitative analysis. • Partner closely with Product Managers, Engineers, and senior stakeholders to translate data insights into actionable narratives and strategies. • Lead efforts to automate data management and reporting processes, collaborating with Business Intelligence and Data Engineering teams. • Champion a hypothesis-driven approach, overseeing product A/B testing and funnel optimization to de-risk development.

• Support the execution and optimization of existing customer and remarketing retention marketing strategies through data analysis, reporting, measurement, and testing. • Collaborate across Marketing, Risk, Product, and Data Science teams to enhance retention strategies while ensuring compliance and data quality. • Analyze and optimize marketing campaigns across Email, SMS, Push, and Authenticated channels. • Conduct audits of marketing data for accuracy, compliance, and consistency with credit policy. • Develop, optimize, and maintain data and reporting solutions, including SQL tables, Power BI dashboards, and automated reporting views. • Perform deep-dive analysis on large datasets to uncover insights that improve targeting, messaging, and channel performance.

• Unify data from key sources (Personio, Lever, 15Five) into a trusted source of truth with high standards for data quality, documentation, and GDPR compliance. • Own core People metrics and build the dashboards that help leadership move from "what happened" to "what to do next" through deep-dive analysis. • Act as a strategic partner to senior leaders, translating business questions into measurable insights and raising overall data literacy across the organization. • Turn survey and feedback signals into clear recommended actions while building scalable reporting processes that reduce manual work.