Associate Director/Director, Computational Test Development

Precede•Cambridge, MA

22d•$180,000 - $240,000

About The Position

Precede Biosciences is seeking an Associate Director- or Director-level computational scientist to lead the analytical and regulatory dimensions of diagnostic test development. Reporting to the Senior Director of Computational Test Development, this role supports the advancement of an epigenomics-based liquid biopsy platform from late-stage development through FDA regulatory submission. The position leads analytical strategy and bioinformatics infrastructure verification for validation programs, interprets complex data, guides computational pipeline execution, and authors regulatory documentation in partnership with laboratory, clinical, and regulatory teams. The work includes developing computational approaches to characterize test performance, assessing NGS and epigenomic data quality, executing verification and validation analyses, and translating results into documentation suitable for FDA submissions. Precede Biosciences describes its platform as an advanced, minimally invasive epigenomics platform intended to support research and development of medicines and the use of approved medicines across conditions including cancer. The company emphasizes purpose, teamwork, excellence, individual initiative, accountability, and delivery. Compensation is $180,000–$240,000 annually, with the specific range dependent on level: $180,000–$215,000 for Associate Director and $215,000–$240,000 for Director. Final compensation depends on qualifications, experience, and geographic location. Employees are also eligible for performance bonuses, equity participation, and comprehensive health benefits.

Requirements

PhD in computational biology, bioinformatics, biostatistics, or a closely related quantitative field.
4–9 years of industry experience in regulated diagnostics, liquid biopsy, or IVD development.
Proven experience working under a formal Quality Management System, such as ISO 13485 or 21 CFR Part 820.
Hands-on experience contributing to regulatory submissions, such as Pre-Subs, De Novo, or 510(k); applicants are asked to describe their specific role and submission type in their cover letter or CV.
Solid understanding of analytical validation frameworks, including CLSI EP guidelines, FDA IVD/CDx guidance, and CAP/CLIA requirements.
Fluency in R and/or Python for statistical modeling, data analysis, and reproducible reporting.
Strong communication skills and demonstrated ability to present and defend analytical validation strategies to internal leadership, scientific advisors, and regulatory stakeholders.
Ability to take autonomous ownership of projects, adapt to evolving information, and execute effectively in an entrepreneurial environment.

Nice To Haves

Direct experience with advanced NGS modalities, such as cell-free DNA, ChIP-Seq, or epigenomic signal processing.
Experience in a fast-paced, cross-functional R&D environment.

Responsibilities

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 and support coordinated optimization of assay and diagnostic performance.
Lead computational execution of verification and validation protocols, statistical analysis plans, 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, and use it to inform study design decisions.
Develop and apply statistical methods for diagnostic characterization, including LOD/LOQ, reproducibility, thresholding, guardbanding, 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.
Partner with laboratory development, clinical operations, and regulatory affairs to ensure scientific and regulatory alignment across programs.
Contribute to clinical study design, including sample size calculations, endpoint selection, and prespecified statistical analysis plans informed by analytical validation pilot data.