• Analyze large-scale wearable and physiological time-series data (e.g., sleep, activity, HR/HRV, temperature) to answer focused research questions in sleep, women’s reproductive health, cardiometabolic health, and movement. • Summarize results in figures, tables, and short written reports for internal stakeholders and potential external dissemination (e.g., abstracts, posters, manuscripts). • Collaborate with Health Science, Data Science, and Product partners to translate findings into clear, actionable insights relevant to Oura members and future product features. • Support literature reviews and contextualization of findings within current evidence to strengthen research narratives.

• Build and maintain data pipelines integrating subscription and membership data from source systems to provide a complete view of the member lifecycle and value. Ensure data quality, lineage, and governance standards for membership data systems. • Build predictive models to understand drivers of member retention, churn, reactivation, and LTV by segment, channel, and cohort. • Lead the design, implementation, and analysis of A/B tests and other experiments across pricing, packaging, and lifecycle communications to quantify impact and inform membership strategy and roadmap decisions. • Partner with Marketing, Finance, and Product teams to design and evaluate offers that improve acquisition efficiency and member retention, and to integrate these learnings into long-term strategic roadmaps. • Build models to optimize membership growth and retention, informing business decisions to strategically optimize financial decisions. • Leverage data engineering and analytical skills to transform data into actionable and reportable insights. • Develop dashboards and reporting tools to visualize membership funnel KPIs, cohort performance, and the impact of product/business changes on member outcomes.

• Design, develop, and deploy Machine Learning and Generative AI solutions • Build and optimize statistical and predictive models • Develop and manage LLM-based and agentic AI applications • Implement NLP/NLU solutions and chatbot applications using Dialogflow CX • Work with Vertex AI and other GCP services (GCS, Pub/Sub, Dataflow) • Utilize BigQuery for data analysis and model training workflows • Implement A/B testing and experimentation frameworks • Collaborate with engineering and product teams to deliver scalable solutions

• Serve as a senior analytical leader, embedding yourself deeply in product and business data to uncover insights and drive actionable recommendations. • Champion and drive the organizational shift toward a data-driven culture. • Own the advancement of experimentation capabilities, train analysts and data scientists on causal methodologies. • Provide leadership with a clear, reliable understanding of true impact and causality. • Define, champion, and execute a strategic roadmap for measuring impact across PandaDoc. • Design, implement, and analyze complex A/B tests and advanced experimentation methods. • Apply causal inference techniques to scenarios where randomized controlled trials are infeasible. • Conduct complex, proactive, and exploratory analysis to discover user behavior and key metric changes. • Define, instrument, and govern a unified Key Performance Indicator framework.