Confidential Careers · 1 week ago
Senior Staff Data Analyst
Confidential Careers is seeking a Senior Data Analyst who will develop and improve statistical and algorithmic methods for NGS-based variant detection and MRD calling. The role involves collaborating with various teams to enhance tumor/normal variant calling and implement algorithms in production-quality code.
Human ResourcesRecruiting
Responsibilities
Improve and extend somatic variant calling algorithm for tumor tissue and cfDNA-based mutation detection
Develop and validate MRD calling algorithm
Design benchmarking, evaluation and QC methods
Lead trouble-shooting efforts; drive root-cause analyses and fixes
Implement algorithms in production-quality code and collaborate with engineering to integrate into pipelines and workflows
Work with assay development on new technologies and assay iterations that require custom analysis and algorithm development
Document methods and results and communicate findings and trade-offs to technical and cross-functional stakeholders
Qualification
Required
PhD in Statistics, Biostatistics, Computer Science, Bioinformatics, Computational Biology, Applied Mathematics, or related field, plus relevant postdoctoral or industry experience
Strong foundation in statistical inference and modeling; comfort with uncertainty quantification and decision thresholds
Prior experience with genomics, WGS or large-scale NGS data; familiarity with sources of noise
Demonstrated implementation skills in Python (and/or a performance language such as C++/Rust/Java), including writing maintainable, testable code
Familiarity with standard genomics formats and tooling (FASTQ/BAM/CRAM/VCF) and typical processing steps
Familiarity with regulated product development (e.g., FDA, IVD), including documentation practices, validation expectations, and design controls
Strong communication and collaboration skills, with the ability to work effectively across research, engineering, and assay development teams
Preferred
Experience with cfDNA analysis and/or MRD detection, including low-frequency variant calling or epigenetics analysis
Machine learning experience (e.g., classification under class imbalance, model evaluation and calibration)
Experience collaborating directly with assay development teams and experimental design/analysis planning