• Responsible for ensuring accurate, timely, and efficient reporting and input of data related to all core business functions • Supervise, direct, coordinate, evaluate and ensure proper functioning of the IT support team, data analysis team and reporting unit • Ensure the timeliness and accuracy of internal and external report deliverables • Manage scheduled and ad hoc reporting needs of the organization • Execute and manage the completion of large reconciliation tasks • Responsible for the quality and completeness of data in core systems by performing and overseeing the auditing of data • Ensure consistency and optimal utilization of reporting, reporting processes, systems, performance metrics, data analysis, and overall operational functions • Oversee IT support systems at all call center locations including telephony, telecom liaison, hardware and software • Oversee large systems and data related projects • Lead and execute complex data related analytical projects to drive business decisions and efficiencies

• Analyze complex datasets to identify trends, risks, and performance insights • Write advanced SQL queries to extract, transform, and validate data • Partner with data engineers to improve data quality, integrity, and metric definitions • Develop and maintain dashboards and reports using Power BI or similar BI tools • Translate business questions into measurable KPIs and reporting frameworks • Document data definitions, calculations, assumptions, and methodologies • Support predictive and AI-enabled analytics initiatives in partnership with data science teams • Contribute to data governance efforts across systems of record • Use tools such as dbt, Airflow, and Git to support reliable data workflows • Present findings in clear, structured formats for both technical and non-technical audiences

• Closely support stakeholders in making data-driven decisions • Work with different departments and business lines • Gather requirements, analyze large-scale real-time data, and prepare insights • Design, develop, and extend data model layers for optimized calculations • Craft code that meets internal standards and maintain these standards via code reviews • Collaborate with Data Engineers, Data Scientists, and Business Analysts • Prototype and coordinate data visualizations

• Define and execute a unified analytics strategy across Marketing and Product, including shared metrics, measurement frameworks, and dashboards that serve as a single source of truth and connect marketing investment to product adoption, usage, and customer outcomes. • Build clear operating rhythms and ways of working that close historical gaps and help Marketing and Product make consistent, data-informed decisions. • Partner with Marketing and Product leadership, including the Chief Product & Marketing Officer and other senior stakeholders, to provide actionable insights and executive-ready recommendations that shape go-to-market plans, product launches, roadmap prioritization, and user experience improvements. • Solve complex analytics problems across both functions, including attribution modeling, lead scoring optimization, campaign and event effectiveness, product adoption and feature usage analysis, and analytics for AI-powered features (including instrumentation, usage, and cost drivers). • Build and maintain forecasting and scenario modeling frameworks in partnership with Finance, Product, and go-to-market leaders, tying pipeline, recurring revenue, and usage or consumption models to planning and investment decisions. • Establish and scale an experimentation program across Marketing and Product, setting standards for hypothesis design, test methodology, instrumentation requirements, and clear readouts that translate results into decisions. • Build strong partnerships with data engineering, engineering, and legal, privacy, and security teams to translate business questions into technical requirements, prioritize telemetry and data model work, and improve reliability, quality, accessibility, and compliance in the analytics stack. • Hire, mentor, and develop leaders and team members, raising the bar for strategic thinking, stakeholder partnership, and end-to-end ownership across the analytics organization.