Senior Staff Data Analyst

As a Senior Data Analyst, you will develop and improve statistical and algorithmic methods for NGS-based variant detection and MRD (minimal residual disease) calling. You will focus on tumor/normal variant calling in tissue as well as low-frequency variant detection in cfDNA, partnering closely with assay development, bioinformatics engineering, and R&D teams. The ideal candidate brings strong statistical modeling skills, hands-on implementation experience, and prior exposure to WGS or large-scale sequencing data. Experience with machine learning and regulated (FDA/IVD) environments is a plus.

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.

Requirements / Qualifications

• 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 Qualifications

• 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.