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Karius is a venture-backed clinical metagenomics company developing advanced diagnostic solutions for infectious diseases using genomics and AI. The company's platform detects microbial cell-free DNA in blood to identify over 1,000 pathogens, helping physicians make rapid treatment decisions.
The Staff Biostatistician II will independently design, analyze, and interpret clinical, observational, translational, and research studies with minimal guidance. This is a senior individual contributor role reporting to the Director of Clinical Statistics & Data Management.
Key Responsibilities:
- Independently perform statistical analyses for clinical studies, product development, and evidence-generation efforts
- Partner with clinical and scientific stakeholders to define study objectives, endpoints, hypotheses, and statistical methodologies
- Develop comprehensive statistical analysis plans, including sample size/power calculations, analysis populations, and sensitivity analyses
- Analyze clinical, observational, laboratory, and real-world datasets using appropriate statistical techniques
- Support design and analysis of prospective and retrospective clinical studies
- Develop and validate statistical models for diagnostic performance and clinical outcomes
- Analyze diagnostic performance measures (sensitivity, specificity, diagnostic value, agreement measures)
- Handle complex data structures including longitudinal data, survival outcomes, missing data, and confounding
- Collaborate with Data Science, Bioinformatics, Clinical Development, Medical Affairs, and R&D teams
- Review datasets and analysis outputs for accuracy, completeness, and statistical validity
- Interpret findings and communicate results to technical and non-technical audiences
- Contribute statistical content to study reports, abstracts, manuscripts, regulatory materials, and presentations
- Develop robust, reusable statistical programs and documentation supporting reproducible analyses
- Support continuous improvement of statistical processes and analytical approaches
Travel up to 15% for team events. Work performed in office, lab, or clinical environment with extended periods of sitting/standing.
Requirements:
- Master's degree in Biostatistics, Statistics, Epidemiology, Applied Statistics, or related quantitative field (PhD preferred)
- 3–5 years of relevant biostatistics experience in biotechnology, diagnostics, pharmaceuticals, healthcare, academia, or related life sciences
- Experience designing and analyzing clinical, observational, or translational research studies
- Experience developing statistical analysis plans with study endpoints, sample size/power calculations, analysis populations, and statistical methodologies
- Strong knowledge of statistical methods: regression analysis, categorical data analysis, longitudinal analysis, survival analysis, missing data handling, and confounding adjustment
- Proficiency with diagnostic test performance measures (sensitivity, specificity, diagnostic value, agreement measures) preferred
- Experience analyzing highly multiplexed clinical assays
- Proficiency in statistical programming with R and/or SAS required; Python and SQL preferred
- Experience with complex clinical, biological, genomic, or real-world datasets
- Strong understanding of data quality, analytical reproducibility, statistical validation, and documentation practices
- Experience contributing statistical analyses to clinical study reports, abstracts, manuscripts, presentations, or regulatory submissions
- Ability to independently manage statistical analyses and provide guidance to cross-functional partners
- Strong analytical, problem-solving, and critical-thinking skills
- Excellent written and verbal communication skills for complex statistical concepts to diverse audiences
- Ability to manage multiple priorities in fast-paced, cross-functional environment
- Familiarity with regulatory requirements, Good Clinical Practice (GCP), and statistical practices in regulated life sciences environments preferred
- Demonstrated ability to work independently while recognizing when to seek input or escalate
- Strong attention to detail with commitment to accuracy, quality, and scientific rigor
- Collaborative and proactive approach to cross-functional work
- Ability to navigate ambiguity and adapt to evolving priorities
- Demonstrated accountability and ownership for assigned work
- Commitment to continuous learning and improvement
