Associate Director/Director, Computational Test Development

What You'll Bring

• PhD in computational biology, bioinformatics, biostatistics, or a closely related quantitative field. Direct experience with advanced NGS modalities (e.g., cell-free DNA, ChIP-Seq, or epigenomic signal processing) is highly preferred.
• 4–9 years of industry experience in regulated diagnostics, liquid biopsy, or IVD development, ideally within a fast-paced, cross-functional R&D environment.
• Proven track record working under a formal Quality Management System (ISO 13485, 21 CFR Part 820).
• Hands-on experience contributing to regulatory submissions (such as Pre-Subs, De Novo, or 510(k) tracks). Please describe your specific role and submission type in your cover letter or CV.
• Solid grasp of analytical validation frameworks, including CLSI EP guidelines, FDA IVD/CDx guidance, and CAP/CLIA requirements.
• Fluency in R and/or Python for robust statistical modeling, data analysis, and reproducible reporting.
• Strong communication skills with a demonstrated ability to present and defend analytical validation strategies to internal leadership, scientific advisors, and regulatory stakeholders.
• Startup mindset: You thrive when taking autonomous ownership of projects, remain adaptive under evolving information, and execute effectively in an entrepreneurial environment.

What You'll Do

Analytical Validation & Regulatory Execution

• Design and develop computational approaches for characterizing the performance of existing and new epigenomic tests.
• Define and implement metrics and analyses to assess NGS and epigenomic data quality to enable coordinated optimization of assay and diagnostic performance.
• Lead the computational execution of verification and validation protocols, statistical analysis plans (SAPs), and performance summary reports to meet FDA evidentiary standards.
• Translate complex computational results into clear, well-organized regulatory documentation for FDA submissions.
• Stay current on FDA guidance for IVDs, companion diagnostics, and evolving LDT oversight to actively inform study design decisions.

Statistical & Bioinformatics Analysis

• Develop and apply statistical methods for diagnostic characterization, including LOD/LOQ, reproducibility, thresholding, gaurdbanding, and clinical utility endpoints.
• Support and optimize robust, reproducible analysis pipelines—ensuring code traceability and standardization from raw NGS data through regulatory-grade outputs.
• Identify and systematically address sources of variability, bias, and technical confounding across the computational workflow.

Cross-Functional Collaboration

• Partner closely with laboratory development, clinical operations, and regulatory affairs to ensure absolute scientific and regulatory alignment across programs.
• Contribute to clinical study design—including sample size calculations, endpoint selection, and pre-specified SAPs using data-driven insights from analytical validation pilots.