Associate Scientist / Scientist I, Computational Test Development

What You'll Do

Assay Characterization & Validation 

• Execute data analyses supporting assay characterization across multiple epigenomic and NGS-based diagnostic tests — from raw data processing through performance metric generation 

• Design and implement quality assessment frameworks to evaluate assay and pipeline performance, including QC metric definition, threshold setting, and failure mode identification 

• Run and interpret validation experiments in close coordination with wet lab and senior computational team members, contributing to study execution against pre-defined protocols 

• Pursue defined research questions semi-independently — taking a scoped problem, designing the analytical approach, executing, and returning well-documented results 

In Silico Simulation & Thresholding 

• Design and run in silico simulations to model assay behavior under variable conditions — including signal dropout, coverage non-uniformity, and input DNA variability 

• Develop and apply statistical approaches to threshold setting and performance boundary definition, supporting limit of detection and analytical range characterization 

• Systematically explore parameter sensitivity across bioinformatics pipelines to assess model robustness and inform feature selection 

Regulatory Support & Communication 

• Produce clear, thorough documentation of all analyses code, methods, results, and interpretation to the standard required under design controls 

• Contribute to the authoring of SOPs and analytical summary reports  

• Partner closely with wet lab scientists to ensure computational analyses are grounded in experimental reality and that results are communicated in accessible, actionable terms 

• Present analytical findings clearly in team meetings and cross-functional settings  

• Contribute to a collaborative team environment by sharing code and knowledge openly and proactively 

Who You Are

• MSc in computational biology, bioinformatics, biostatistics, or a closely related quantitative field with 3–4 years of industry or post-graduate research experience in a data-intensive biological or biomedical setting, Ph.D. preferred 

• Strong proficiency in R and Python for data analysis, visualization, and reproducible reporting — you write, own, and document your own code 

• Experience with cloud computing environments (AWS) for running scalable analyses  

• Demonstrated ability to execute analytical plans with precision and efficiency, managing multiple tasks without a drop in quality or documentation standards 

• Familiarity with NGS data types and standard processing pipelines — alignment, QC, coverage analysis, or equivalent 

• Clear and organized communicator — written documentation, results presentations, and cross-functional interactions alike 

• Comfortable working in a fast-paced startup environment, following defined protocols while contributing ideas for improvement 

Nice to have: 

• Exposure to regulated environments — CLIA, CAP, FDA IVD, or design controls in any form 

• Experience with epigenomic data types — methylation, cfDNA, chromatin accessibility, or ChIP-seq 

• Familiarity with statistical thresholding or limit of detection frameworks for diagnostic applications 

• Experience contributing to SOPs, validation reports, or other regulated documentation