About this role
Role Overview
Apply advanced computational genomics and statistical bioinformatics expertise to realistic, multi-step scientific data-analysis work spanning quantitative biology and translational biomedicine. You will independently turn complex biological and biomedical datasets into reproducible analyses and clearly interpreted findings while collaborating with scientists and AI research specialists.
Key Responsibilities
- Complete multi-step scientific data-analysis tasks in computational genomics, quantitative biology, and translational biomedicine.
- Inspect datasets independently, perform quality control and exploratory analysis, select suitable statistical methods, and conduct analyses in R and Python.
- Navigate ambiguous research workflows by identifying critical analytical decisions, potential confounders, and limitations in available data.
- Use scientific software, code, and command-line tools to produce reproducible analyses and structured final outputs.
- Interpret results in relation to the underlying biological or translational question, communicating assumptions, uncertainty, and conclusions clearly.
- Collaborate with a multidisciplinary team of scientists and AI research specialists.
Qualifications
- PhD in computational biology, bioinformatics, statistical genetics, quantitative biology, biostatistics, genomics, or a closely related field.
- Deep hands-on experience analyzing biological or biomedical data, particularly genomics, sequencing, single-cell, population genetics, QTL/GWAS, or related omics datasets.
- Professional fluency in R and Python, including the ability to write, debug, and explain analysis code.
- Strong foundation in statistical modeling, experimental design, quality control, and scientific inference.
- Experience independently completing multi-step computational research workflows, from raw or messy data through final interpretation.
- Clear scientific writing skills and the ability to document methods, assumptions, and results precisely.
- Familiarity with reproducible research practices, such as notebooks, scripts, version control, or workflow tools, is preferred.
Work Terms
- Remote, hourly, project-based engagement.
- Open to qualified experts globally.
Compensation
- $85 per hour.