Associate Director of Bioinformatics

About the role

The will lead a team of Bioinformatics Scientists within the Women's Health and Organ Health research organization, owning the scientific planning and execution of research and assay-development initiatives for diagnostic projects. This role is responsible for creating production-ready pipeline components while managing team professional growth, research strategy for new product development, and the critical handoff of research work into production environments. The position requires deep expertise in algorithm and assay development, NGS data processing across multiple modalities, and the full life cycle of diagnostic product research and development within 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 in close collaboration with R&D, Product, and Laboratory Directors. Success in this role will be defined by your ability to set the technical vision and execution standards that enable high-impact diagnostic discoveries.

Key facts

What you'll do

• Lead and mentor a team of Bioinformatics Scientists, owning their professional growth, responsibilities, and the standard the team holds itself to in a regulated environment.
• Own the research strategy behind new product development, from scoping through execution, and work with cross-functional stakeholders on what the team takes on and in what sequence.
• Lead bioinformatics analysis for assay development and optimization, and troubleshoot experiments alongside laboratory scientists, spanning multi-omic approaches including methylation and fragmentomics and other cell-free DNA (cfDNA) derived features.
• Span short-read and long-read sequencing and both hybrid-capture and amplicon target enrichment methodologies to support comprehensive assay design and troubleshooting.
• Partner with laboratory teams on study design at the research and feasibility stage, covering new technology assessment, optimization, and performance determination to ensure the resulting data holds up before anyone builds on it.
• Advise and prototype improvements to analysis pipelines, including variant detection, quality control, and modality-specific processing such as methylation calling, fragment-size and end-motif analysis, error suppression for deep targeted panels, and structural-variant calling.
• Move research prototypes into stable production workflows, holding the team to software engineering practices 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 is redirected to high-value scientific work.
• Set the standard for correct use of AI agents in the workflow, defining what an agent may conclude on its own and what requires a scientist to sign off, without screening for prior experience and providing tooling and ramp time.
• Work with data science, molecular biology, pipeline engineering, biostatistics, quality assurance, and laboratory operations on new products and on the transition of research work into production, acting as the subject-matter expert and explaining findings and the roadmap clearly at every level of the company.
• Establish a research roadmap for the team with visible progress against it outside the team, demonstrating independent advice and guidance in cross-functional settings.
• Implement new analysis methods from your team within production code and demonstrate expected performance on benchmark studies to validate scientific rigor.
• Become trusted experts that other functions direct their hard questions to, and independently support decision making through clear communication and actionable insights.
• Normalize AI agent-assisted work on the team, with defined standards for adoption and oversight that balance innovation with scientific accountability.

Requirements

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Mathematics, Engineering, Biostatistics, or a related field. (An M.S. with relevant experience may be considered in lieu of a Ph.D.)
• Demonstrated experience leading and mentoring a team of scientists in a research or product development environment.
• Extensive experience with NGS data processing across multiple modalities, including but not limited to whole genome sequencing, exome sequencing, and targeted sequencing.
• Deep expertise in algorithm development and assay development for NGS-based diagnostics, with a strong track record of translating bioinformatics findings into robust assays.
• Proven experience working with multi-omic data types, including methylation and fragmentomics, particularly in the context of cell-free DNA (cfDNA) analysis.
• Hands-on experience with both short-read and long-read sequencing technologies, as well as hybrid-capture and amplicon target enrichment methods.
• Strong background in CLIA-regulated assay development and diagnostic research, with an understanding of compliance and quality standards.
• Experience with study design and data quality assessment at the research and feasibility stage, including new technology evaluation and performance determination.
• Proficiency in prototyping and improving analysis pipelines, with skills in variant detection, quality control, and modality-specific processing.
• Demonstrated ability to move research prototypes into production-ready workflows with robust software engineering practices.
• Excellent cross-functional communication skills, with the ability to serve as a subject-matter expert for data science, molecular biology, laboratory operations, and biostatistics teams.
• Comfort working in a fast-paced, regulated environment where scientific rigor and reproducibility are paramount.
• Willingness to set and uphold standards for AI tool usage in scientific workflows, including defining acceptable autonomy and oversight mechanisms.

Nice to have

• Prior experience with AI agents in scientific or bioinformatics workflows.
• Background in developing or deploying diagnostic assays in a CLIA-regulated laboratory.
• Experience with fragmentomics or methylation profiling at scale in clinical research settings.

Practical notes

• This is a US Remote position.
• Full-time employment with standard working hours as defined by Natera policies.
• No specific travel requirements are indicated in the source.
• No visa sponsorship details are provided in the source.
• No application deadline is specified in the source.