• Partner with Sales, Marketing, Operations, and CSM leaders to define and operationalize Growth & Retention KPIs (acquisition, activation, expansion, churn, LTV, NRR). • Build and maintain a B2B Customer 360 data model integrating product usage, contracts, billing, support, engagement, and operational signals. • Design, build, and maintain analytics data models and semantic layers that power dashboards and AI-driven insights. • Build executive and operational dashboards focused on growth performance and customer health. • Develop churn prediction models, customer health scores, and expansion propensity models. • Identify leading indicators for churn, renewal risk, and upsell opportunities. • Leverage AI/ML and LLM-based techniques for: Automated insight generation, Anomaly detection, Opportunity and risk scoring, Natural language analytics (e.g., text-to-SQL, insight summaries) • Ensure high data quality, reliability, and observability in collaboration with data engineering. • Drive best practices in analytics engineering (testing, version control, documentation, code reviews). • Influence analytics strategy and roadmap for Growth & Retention and Customer 360.

• Develop software solutions supporting quantitative analysis and modeling for credit ratings data • Analyze NRSRO data disclosures for compliance with applicable rules and statutes • Maintain analytical frameworks for utilizing data and quantitative analyses to identify potential areas for further inquiry • Conduct data-driven research related to the credit rating industry; summarize findings concisely through charts and graphs • Test deployment and functionality of internal systems and applications after new features are added • Document and quality-assure all project work prior to client delivery • Attend meetings with agency staff, securities industry participants, other government agencies, and relevant external organizations as needed • Contribute meaningfully to building Peregrine as an enterprise — whether through leading business development pursuits, developing internal tools or intellectual property, mentoring colleagues, or maintaining an active publication record • Collaborate with firm leadership to identify and drive initiatives that strengthen Peregrine's capabilities and market position

• Collaborate with data engineering, analytics, product, and marketing teams to design and implement reliable, scalable data models and transformation pipelines. • Develop and maintain dbt models, macros, and documentation that ensure data accuracy, reusability, and clarity across the organization. • Partner with business stakeholders to translate analytical needs into well-structured datasets that support reporting and self-service analytics. • Support and uphold best practices for data modeling, testing, version control, and documentation across analytics workflows. • Proactively identify and address issues in data quality, model performance, and pipeline efficiency. • Contribute to the standardization of metrics, definitions, and semantic layers to ensure consistent reporting across business units. • Participate in code reviews and knowledge-sharing to continuously improve team processes and data craftsmanship. • Stay current with modern data tools, frameworks, and best practices to help evolve our analytics engineering stack.

• Establish the foundation of LiveKit's analytics practice • Translate business concepts into robust data models • Create actionable KPIs • Enable data-driven decision making across the organization • Use AI coding assistants extensively and evolve AI development workflows • Resist the urge to over-engineer • Spend significant time with stakeholders to memorialize business logic and create trusted metrics • Ensure everything built needs clear documentation for users and AI systems • Follow engineering best practices with PR reviews and automated testing • Comfort with ambiguity and rapid iteration