• Design Scalable Financial Data Solutions – Develop robust data models, pipelines, and reporting systems that drive informed decision-making across teams. • Ensure Compliance & Governance – Embed “compliance by design” principles to uphold SOX standards, streamline audits, and enforce data governance. • Champion Data Integrity – Establish rigorous validation and monitoring frameworks to ensure accuracy, consistency, and reliability in financial data. • Lead & Develop Talent – Build, mentor, and scale a high-performing analytics team, fostering a culture of innovation and excellence. • Drive Cross-Functional Collaboration – Partner with Finance, Accounting, and Engineering to align data strategies with business objectives and operational needs. • Leadership Communication – Presenting insights and recommendations to senior leadership in a clear, impactful manner. • Cross Functional Collaboration – Partnering with stakeholders and product managers to translate requirements into scalable system designs.

• Lead end-to-end delivery of strategic analytics programs spanning multiple teams or business domains. • Architect scalable and reusable analytics solutions, including data pipelines, semantic models, and KPI frameworks. • Design and evangelize measurement strategies that drive alignment on goals and performance metrics. • Guide business-critical decision-making with deep, proactive insights using SQL, Looker, and statistical modeling. • Serve as an expert advisor to executives and senior leaders on data strategy and analytics capabilities. • Influence cross-functional partners to prioritize and integrate data-informed decision-making across initiatives. • Drive the evolution of internal analytics infrastructure, standards, and governance. • Coach and mentor analysts across teams; lead communities of practice and best-in-class knowledge sharing. • Represent the Analytics function in cross-org strategic planning and OKR development.

• Define and Govern Analytical Strategy: Establish the multi-quarter analytical roadmap for a major business area (e.g., Clinical, Growth, or Operations), translating strategic objectives into measurable, actionable data initiatives. • Architect Data Models: Serve as the principal steward of Synapticure’s data models and semantic layers (dbt/Snowflake), ensuring scalability, performance, and data integrity across the enterprise. • Lead Cross-Functional Initiatives: Manage complex, high-impact projects that require integration of diverse data sources and alignment across Product, Clinical, Finance, and Operations teams. • Strategic Partnership: Act as a trusted advisor to senior and executive leadership—framing key questions, guiding methodology, and delivering data-driven insights that shape company direction. • Mentorship & Team Development: Provide technical mentorship to other analysts, establish standards for analytical rigor and reproducibility, and elevate the analytical maturity of the entire organization. • Define and Govern Key Metrics: Create and maintain consistent definitions for enterprise-level KPIs to ensure alignment and accuracy across teams. • Storytelling with Data: Communicate analytical findings through compelling narratives that connect technical results to business and clinical impact. • Champion Data Integrity: Lead by example in maintaining high standards of quality, governance, and documentation across all analytical outputs and infrastructure.

• Analyze player journeys, game mechanics, and engagement patterns to guide game development and feature design. • Conduct deep-dive investigations and exploratory analyses of KPIs to uncover growth opportunities and friction points. • Communicate findings clearly through impactful visualizations and concise storytelling tailored to stakeholders. • Collaborate with stakeholders to define success metrics, experiment frameworks, and data needs. • Design and execute experiments (e.g., AB tests) based on player insights and team priorities. • Drive improvements to our BI ecosystem and data pipelines to support scalable, product-focused analytics. • Own the full analytics cycle: from identifying questions to delivering insights and driving decisions. • Proactively identify trends, anomalies, and emerging behaviors through ongoing monitoring and analysis. • Contribute to a culture of data curiosity and excellence by supporting data democratization across teams. • Apply a product-centric mindset — focusing on delivering business value, not just tasks or reports.