Biostatistician, ML & Genomics in Diagnostics

PreludeDx; Laguna Hills (CA); On-site; USD 110,000 - 160,000; Full time

Job summary

PreludeDx is seeking a highly skilled Biostatistician to support development and validation of molecular diagnostics by integrating genomic and proteomic data. You will apply advanced statistics and ML to high-dimensional data, ensure QA of NGS pipelines, and collaborate across assay development, bioinformatics, and clinical research.

The role includes designing statistical models, performing variant analysis, and ensuring reproducible analyses with R and SAS support for regulatory submissions.

Qualifications

• Experience in CLIA/CAP accredited clinical labs.
• Expertise analyzing NGS data (WES, RNA-Seq, panels).
• Proficient in R; SAS for regulatory data is a plus.
• ML techniques applied to biomedical data.
• Familiar with FASTQ, VCF, BAM, GTF formats.

Responsibilities

• Release bioinformatic analyses to support clinical operations.
• Build statistical models and ML algorithms for diagnostics.
• Analyze NGS datasets including variant calling and annotation.
• Develop QA protocols for NGS data pipelines.
• Integrate multi-omic data with cross-functional teams.
• Support study design and regulatory submissions.
• Document analyses, validation, and pipeline specs.
• Write reproducible R code; SAS preferred for regulated data.
• Contribute to publications and scientific communications.

Skills

NGS data analysis

R programming

Machine learning

Bioinformatics pipelines

Cloud computing

Data integration

Git

Regulatory submissions

Communication skills

Education

Biostatistics/Bioinformatics degree

Tools

R

SAS

Bioconductor

AWS

GCP

Job description

PreludeDx is seeking a highly skilled Biostatistician to support development and validation of molecular diagnostics by integrating genomic and proteomic data. You will apply advanced statistics and ML to high-dimensional data, ensure QA of NGS pipelines, and collaborate across assay development, bioinformatics, and clinical research.

The role includes designing statistical models, performing variant analysis, and ensuring reproducible analyses with R and SAS support for regulatory submissions.