• 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.

• Configure internal queues in the CRM for distributing tickets to agents. • Analyze and optimize prioritization logic, SLA paths, and fallback routing. • Support special scenarios: escalations, VIP cases, language queues, shift-based routing. • Perform regular audits of rule correctness and their impact on SLA and workload. • Monitor key metrics: SLA, AHT, backlog, occupancy, shrinkage. • Detect anomalies in data and investigate root causes of deviations. • Analyze the impact of queue and process changes on service metrics. • Prepare regular performance analytics and reports for management. • Calculate required agent headcount based on forecasts and SLA. • Model "what-if" scenarios: marketing activities, SLA changes, new processes or products. • Evaluate schedule effectiveness and recommend optimal resource allocation. • Build time series forecasts for incoming tickets, chats, and calls. • Identify seasonal patterns, spikes, and holiday effects. • Prepare short-term and long-term forecasts (interval, weekly, monthly horizons). • Update forecasts considering product changes, marketing activity, and process updates. • Write SQL queries to retrieve data from the analytics database. • Collect data from multiple sources (CRM, BI systems, queue logs). • Prepare and clean datasets for forecasting models.