• Own the product vision and roadmap for internal tooling, automation initiatives, and back-office applications. • Lead the company's AI adoption strategy, identifying opportunities to integrate LLMs, machine learning, and intelligent automations to streamline workflows. • Manage the full lifecycle of multiple full-stack applications, balancing the needs of internal operational tools with external customer-facing services. • Coordinate cross-functional efforts to ensure performance, scalability, and security across both internal and external application ecosystems. • Define and manage the data engineering roadmap, partnering with data engineers to build robust pipelines, modern data warehousing solutions, and analytics infrastructure. • Collaborate with engineering leadership to guide the transition toward a microservices architecture, ensuring internal services are scalable, decoupled, and highly performant. • Write clear, technically sound Product Requirements Documents (PRDs), manage backlogs, and run agile sprints with backend and data engineering teams. • Establish success metrics for internal products, focusing on operational efficiency, processing times, automation success rates, and data reliability.

• Drive product outcomes to solve critical business problems • Define vision, strategy, and OKRs for product area • Execute product vision across applications for user groups • Collaborate with legal, compliance, security, and risk teams • Guide creation of user-facing communication related to features • Partner with product leadership to refine vision and strategy • Execute discovery activities with engineering and UX • Conduct end user shadowing and interviews to identify user problems

• Develop Product vision, performance metrics, roadmaps, and clearly communicate this with stakeholders and team members. • Define the business value for the Product and support messaging, communication, and customer outreach as necessary. • Build the Product Backlog, prioritize the backlog based on business value, and continuously refine the backlog. • Prioritizing backlog includes incorporating stakeholder input into product roadmap while effectively negotiating tradeoffs of conflicting priorities based on value to the business and customer. • Breakdown large epics/features and write user stories that convey value to the end user. • Ensure appropriate stakeholders are involved in the Sprint Review. • Ensure team members understand the stories in the backlog and the business value they deliver. • Collaborate with technical leadership in and outside the team to help define the technical roadmap for the Product (several sprints ahead of them). • Engage with customers and stakeholders on a regular basis to gather feedback and refine the future of the Product as a result (including continuous process improvement) and adjust the backlog as needed. • Raise dependencies and roadblocks both internal and external to the team, with support of the Scrum Master and help resolve them if needed. • Scope minimum viable products, considering existing resource constraints and sustained development of the Product. • Participate in sprint ceremonies when needed and work to support the team on a daily basis.

• Product strategy: In partnership with the Head of Product, translate product vision for the omics platform into a credible multi-quarter roadmap for molecular data consumption and analytics. • Define researcher and developer experiences: define and iterate on how computational biologists, data engineers, and enterprise teams query, analyze, and extract insights from omics data at scale. • Lead interoperability requirements: specify the integration layer that connects the omics platform to enterprise analytical environments and other platforms in the omics ecosystem. • Define GUI experiences and consumption-layer APIs that serve diverse user types. • Define agent-ready platform requirements: specify what analytics APIs and data structures must look like to support agentic users. • Define benchmarking requirements: specify the researcher queries, analytical functions, and performance metrics that engineering and product design need to optimize for. • Lead customer and design partner programs: run structured discovery sessions with pharma and biotech partners. • Drive cross-functional execution: serve as the product manager for your engineering pod. Author high-quality Epics and User Stories.