• 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.

• Consult with business customers and understand their analytical needs • Develop technical requirements for reports and analysis • Identify and capture data from internal and external sources • Apply statistical and visualization techniques to analyze structured and unstructured datasets • Use SQL, Python, and business intelligence tools (Qlik,) to create dashboards and visualizations • Create dashboard documentation and training materials • Manage projects and stakeholder relationships effectively.

• Learn to write and optimize SQL queries for reporting and analysis. • Assist in extracting, cleaning, and analyzing data from multiple sources. • Support the development of dashboards and reports using tools such as Power BI, Tableau or Sigma. • Collaborate with team members to translate business requirements into data solutions • Learn team structure and deliver assigned items in established timelines. • Gain an understanding of various product and service datasets, codebases, and business purposes. • Learn to balance and prioritize individual workload across different types of requests. • Learn compliance standards across various product areas.