• Own and evolve data science and analytics architecture across Everstake • Design and maintain scalable data pipelines, metrics layers, and analytical models • Lead technical decision-making across data platforms, BI, and orchestration • Translate blockchain, product, and business problems into clear data solutions • Define data standards, best practices, and development guidelines • Review code, data models, and pipelines for quality, performance, and correctness • Mentor senior data scientists and analysts, provide technical leadership • Partner closely with product, backend, infrastructure, and finance teams • Ensure data reliability, observability, and correctness in production • Actively contribute hands-on where technical depth is required

• Lead a team of mixed technical roles (Data Scientists, Analytics Engineers, and Data Engineers) • Drive the vision and roadmap for the team • Be a strategic thought partner to shape the strategy of the broader Messaging domain • Drive a culture of innovation through collaboration with other leaders

• Lead and deliver the translation of complex biological and clinical questions into actionable analysis plans. • Architect and implement robust data pipelines that integrate large-scale genomic, phenotypic, laboratory, and real-world clinical datasets. • Conduct repeatable data analysis and modeling with a high degree of scientific and statistical rigor, for complex tasks such as understanding patient trajectories, elucidating variant effect, and identifying genotype-phenotype associations. • Write clean, maintainable, and well-documented code following best practices for version control, testing, and scalability. • Prepare technical reports, peer-reviewed publications, and conference presentations to share research outcomes with internal stakeholders and the broader scientific community. • Collaborate closely with both internal and external stakeholders to drive impactful research and development initiatives. • Ensure high standards of data privacy, security, and compliance are maintained in all projects.

• Drive product analytics, production quality management, and experience optimization for Canada’s digital experience. • Collaborate closely with regional product leadership and cross-functional teams. • Perform thorough production testing across the Canada experience. • Monitor error spikes in production, coordinate timely fixes, and safeguard customer experience stability. • Track funnel metrics to measure stability and identify conversion issues. • Partner with the Canada Regional Product Lead to generate funnel analytics and insights.