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Nautilus Biotechnology is developing a single-molecule protein analysis platform to democratize access to the proteome. You will join as a Senior Bioinformatics Scientist to own the analysis side of a new assay modality, working in tight iteration with experimental teams.
In this role, you will partner daily with experimentalists to troubleshoot and optimize protocols, analyze all data types the platform produces (images, fluidics readouts, fluorescence signals, single-molecule outputs), and recommend next steps based on results. You will own result interpretation—determining what data mean, confidence levels, and recommended directions—and work with R&D leadership to frame findings and inform project strategy.
Key responsibilities include designing and building durable analysis pipelines, quality control metrics, and dashboards for the new data type while balancing rapid one-off analyses with reusable tools. You will develop new analytical and statistical approaches for interpreting stochastic single-molecule measurements alongside the bioinformatics team. You will also quickly learn to locate and access assay data across cloud databases, object storage, on-premises servers, and raw instrument output, writing code to parse metadata and manage cloud access.
This is a hands-on role requiring an applied scientist who values progress over perfection, thrives in unfamiliar territory, removes obstacles proactively, and partners effectively with experimental teams. You will report to a Bioinformatics Fellow and work in San Carlos with a minimum of three days in-office required.
REQUIREMENTS:
- PhD in Bioinformatics, Computational Biology, Biophysics, Biochemistry, Biostatistics, or related quantitative field
- Minimum 4 years industry experience
- Track record as applied, hands-on scientist comfortable with imperfect information and unfamiliar challenges
- Hands-on experience analyzing wet-lab experimental data with demonstrated assay development/optimization in partnership with experimental teams
- Ability to own projects end-to-end from experimental design through interpretation and recommendations
- Exceptional written and verbal communication skills, including framing results for leadership and explaining technical findings to non-computational audiences
- Solid foundation in applied statistics (distributions, variability, hypothesis testing, experimental design)
- Proficiency in Python (pandas, NumPy, SciPy) and SQL; experience building both durable pipelines/dashboards and rapid one-off analyses
- Comfortable across local machines, shared servers, and cloud environments (AWS); Linux, Git, and credential management
- Ability to contribute on organized, dynamic team in fast-paced environment
- Strongly preferred: hands-on wet-lab experience
- Preferred: experience with proteomics, fluorescence imaging, single-molecule methods, instrument development, or affinity reagents
- Preferred: probabilistic modeling of stochastic data or protein structural modeling
