Associate Director of Bioinformatics (Women's Health and Organ Health)

Natera is seeking an Associate Director to lead a team of Bioinformatics Scientists in our Women's Health and Organ Health research organization. You will oversee the scientific planning and execution of research and assay-development of diagnostic projects, and you will be responsible for creating production-ready pipeline components. You will manage your team and its professional growth, the research strategy behind new product development, and the handoff of research work into production. The role calls for deep experience in algorithm and assay development, NGS data processing across multiple modalities, and the full life cycle of diagnostic product research and development in a regulated (CLIA) setting. You will evaluate new technologies and NGS assays, implement methods to optimize performance, and help define the product profile from a bioinformatics perspective, with input from R&D, Product, and Laboratory Directors. Primary Responsibilities: Team Leadership and Development: Lead and mentor a team of Bioinformatics Scientists. Own their professional growth, their responsibilities, and the standard the team holds itself to. Research Strategy: Own the research strategy behind new product development, from scoping through execution, working with cross-functional stakeholders on what the team takes on and in what order. Assay Science: Lead bioinformatics analysis for assay development and optimization, and troubleshoot experiments alongside laboratory scientists. This spans multi-omic approaches including methylation and fragmentomics and other cell-free DNA (cfDNA) derived features. It also spans short-read and long-read sequencing and both hybrid-capture and amplicon target enrichment. Study Design and Data Quality: Partner with laboratory teams on study design at the research and feasibility stage, covering new technology assessment, optimization, and performance determination. Make sure the resulting data holds up before anyone builds on it. Analysis Method Improvement: Advise and prototype improvements to analysis pipelines, including variant detection, quality control, and modality-specific processing: methylation calling, fragment-size and end-motif analysis, error suppression for deep targeted panels, and structural-variant calling. Production Readiness and Handoff: Move research prototypes into stable production workflows. Hold the team to software engineering practice, including version control, testing, continuous integration and delivery, and containerization. Automate the routine parts of research data management, pipeline execution, and reporting so the team's time goes to science. Ways of Working: AI is a routine part of the work here. As the leader of this team you set what correct use looks like: what an agent may conclude on its own, and what requires a scientist to sign off. We do not screen for prior experience with these tools, and many strong candidates come from environments where they were restricted; we provide th