• Apply statistical and computational approaches to analyze WGS/WES, proteomics, metabolomics, and clinical data for biomarker discovery. • Conduct rigorous analyses of large-scale population cohorts and biobank datasets to identify genetic variants and causal genes associated with disease outcomes. • Develop and implement machine learning and bioinformatics pipelines to integrate multi-omics data. • Collaborate with interdisciplinary teams, including geneticists, epidemiologists, and clinicians, to interpret findings and guide therapeutic development. • Prepare scientific reports, presentations, and publications detailing research outcomes. • Contribute to the development of novel statistical methods for analyzing high-dimensional biological data.

- Apply **statistical and computational approaches** to analyze WGS/WES, proteomics, metabolomics, and clinical data for biomarker discovery. - Conduct rigorous analyses of **large-scale population cohorts and biobank datasets** to identify genetic variants and causal genes associated with disease outcomes. - Develop and implement **machine learning and bioinformatics pipelines** to integrate multi-omics data. - Collaborate with interdisciplinary teams, including **geneticists, epidemiologists, and clinicians**, to interpret findings and guide therapeutic development. - Prepare **scientific reports, presentations, and publications** detailing research outcomes. - Contribute to the development of **novel statistical methods** for analyzing high-dimensional biological data.

• Own analytics across Pinwheel’s product suite, focusing on conversion optimization and understanding customer and platform-level implementation patterns that drive success • Proactively identify trends, opportunities, and anomalies in product metrics—not just answering data questions; asking better ones • Develop metrics frameworks and KPI dashboards to monitor product performance, conversion funnels, and integration health across hundreds of partners • Partner with EPD and GTM teams to translate insights into action, informing product improvements and go-to-market narratives • Build a deep understanding of customer segments, product placement, and configuration performance to inform best practices for our partners and customers • Enable Sales and Marketing with case studies and metrics that highlight success factors across high-performing customers and integrations • Partner with Engineering and Data teams to ensure proper instrumentation, metric definitions, and data model design • Develop a system to ingest and synthesize qualitative feedback (e.g. Gong calls, Slack feedback, user surveys, and interviews) into unified insights about product opportunities

• Understand detailed usage of products by analyzing user behavior data, translating complex questions into analytical plans, and building robust product metrics. • Run and measure product experiments (A/B tests) from design through interpretation, clearly articulating results and recommendations to stakeholders. • Develop and maintain key performance indicators (KPIs) and operational metrics for product features and overall business health. • Provide actionable insights for Product Managers on user engagement, feature adoption, and growth opportunities to directly inform the product roadmap. • Build deep-dive reports for Executive Leaders on critical business trends and the performance of strategic initiatives, presenting findings in a clear, compelling narrative. • Collaborate with engineering teams on data logging, instrumentation, and ensuring the accuracy of product data pipelines. • Apply statistical modeling and machine learning techniques to solve business problems (e.g., churn prediction, segmentation, propensity modeling). • Design and implement data visualizations and self-service dashboards to democratize data access across the organization. • Partner with cross-functional teams (Product, Engineering, Marketing, Sales) to define data requirements and analytical objectives. • Coach and mentor junior analysts and data scientists on best practices for data visualization, statistical analysis, and clear communication of results.