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.