Specialist Scrum Master

Scrum Master – Disease Biology is a delivery leader and agile coach responsible for driving execution across Disease Biology programs spanning Omics, Multi-Omics, Semantic Graph platforms, and biological research workflows. This role bridges scientific requirements, product strategy, and engineering delivery, enabling teams to deliver scalable, data-driven solutions that accelerate biological insights and therapeutic discovery. The Scrum Master facilitates Agile ceremonies, ensures alignment to program objectives, manages dependencies across teams, and fosters continuous improvement within a complex, data-intensive research ecosystem. 1. Scrum Master / Agile Delivery Lead end-to-end Agile delivery across Disease Biology teams using Scrum and SAFe practices, ensuring disciplined execution against sprint, PI, and program commitments. Facilitate Agile and SAFe ceremonies, including daily stand-ups, sprint planning, backlog refinement, sprint reviews, retrospectives, demos, PI Planning, Scrum of Scrums, and Inspect & Adapt sessions. Track and communicate delivery progress, risks, dependencies, blockers, and metrics such as velocity, burndown, and cycle time to support transparency and predictability. Coordinate across Agile Release Trains, data engineering, platform, scientific, support, and operations teams to manage dependencies, resolve delivery blockers, and support issue resolution for released capabilities. Coach teams toward higher levels of Agile maturity, standardize Agile practices across Disease Biology programs, and foster a culture of collaboration, experimentation, innovation, and continuous improvement. 2. Business Analysis / Scientific Product Delivery Partner with Disease Biology scientists, product owners, product management, solution management, engineering, and platform teams to elicit, refine, and prioritize scientific, technical, and business requirements. Translate scientific and technical needs into structured user stories, acceptance criteria, backlog priorities, and traceability between scientific objectives, business value, research priorities, and delivered solutions. Drive alignment between scientific workflows, including wet lab and computational biology, data platforms, engineering execution, and product roadmaps. Enable delivery of data and analytics solutions across omics pipelines, multi-modal datasets, semantic graph-based knowledge systems, and scalable biological data platforms. Support insights-driven scientific use cases, including target discovery, biomarker analysis, disease modeling, and integration of genomics, transcriptomics, proteomics, and clinical datasets. Serve as a bridge between scientific stakeholders, product teams, and engineering teams by facilitating decision-making, resolving ambiguities, and ensuring clear cross-functional communication.