The posting
At Nautilus, we have a big and important mission: positively impact the health and lives of people around the world by unleashing the potential of the proteome. We are developing a single-molecule protein analysis platform of unprecedented sensitivity, scale, and ease of use that we believe will democratize access to the proteome – one of the most dynamic and valuable sources of biological insight. To accomplish this, we are pursuing hard scientific problems with an entrepreneurial mindset and creating a world-class team of builders, innovators, and dreamers across a wide range of disciplines.
We are actively seeking a talented Senior Bioinformatics Scientist to join our growing team. Turning data generated by our platform into reliable proteomic insights depends on assays that are well designed, well optimized, and well understood. In this role, you will partner closely with assay development, reagent, and platform scientists to design experiments, define what success looks like, and translate results into decisions about how our assays should work – whether that means developing a novel assay, optimizing an existing one, or understanding why a result did not go as expected. Doing this well requires connecting the full story of an experiment: the reagent lots that went in, the experimental design, the raw data, how that data was processed, and whether the statistics support the conclusion. We are looking for someone with exceptional communication skills, comfort accessing data wherever it lives, and a strong understanding of experimental work. This role is broad by design and is well suited to someone with a can-do attitude and a genuine desire to learn, who enjoys variety and gets satisfaction from helping teams make good decisions with data
This position will report to a Bioinformatics Fellow. This position is based in San Carlos, CA. A minimum of three days in the office is required.
Responsibilities
- Partner with scientists to deliver proteoform and proteome assays built on our single-molecule proteomics platform powered by Iterative Mapping.
- Independently analyze Iterative Mapping data end to end – from run metadata through image-processing, protein decoding, and statistical conclusions – then communicate results and recommendations in a clear and actionable manner to all members of the company regardless of their scientific background.
- Optimize assay performance by establishing levers for improving reproducibility and quantitative accuracy.
- Guide experimental design, including controls, replicates, and sample sizes, and conduct sensitivity and power analyses that set acceptance criteria before data is collected.
- Diagnose unexpected experimental results by forming and testing hypotheses that span reagents, instrument, image processing, and algorithms, and feed lessons learned into the next round of assay design.
- Develop and maintain the quality control metrics and reports scientists use to evaluate their runs, setting defensible thresholds and explaining what each metric means and why it matters.
- Access and integrate data wherever it lives, including cloud data warehouses, object storage, on-premises file servers, and experiment metadata records, reconciling inconsistencies as needed.
- Convert recurring analyses into reusable, tested software tools that the broader team can run.
- Work closely and cross-functionally with chemists, engineers, and algorithm developers as part of project teams across the company.
Requirements
- A PhD in Bioinformatics, Computational Biology, Biostatistics, Biophysics, Chemistry, or a related quantitative field.
- A minimum of 4 years of experience in industry.
- A can-do attitude and a desire to learn: eager to take on unfamiliar problems, pick up new domains, and bring ideas forward rather than waiting for requirements.
- Exceptional written and verbal communication skills, including the ability to explain technical findings to non-computational audiences.
- Hands-on experience analyzing data from wet-lab experiments, ideally including assay development or optimization, with a strong understanding of how bench work is performed and what drives assay performance.
- Demonstrated ability to trace complex, real-world data problems from raw data to root cause.
- Solid foundation in applied statistics, including distributions and variability, hypothesis testing, and power/sensitivity analysis.
- Proficient in Python for data analysis and visualization (e.g., pandas, NumPy, SciPy)
- Comfortable working across local machines, shared servers, and cloud environments, including Linux and Git.
- Experience working with AWS data storage and processing services (e.g. Athena, S3) preferred.
- Hands-on bench experience preferred.
- Experience with proteomics preferred.
- Experience moving an assay from early development through production, preferred.
- Experience building dashboards or interactive tools for non-computational users (e.g., Dash, Marimo) preferred.
Nautilus Team Culture
- We are curious go-getters: this is a team of life-long learners who aren’t afraid to tackle the big challenges and we embrace the journey.
- We are detail-oriented: we do great science by working smart and with diligence where we learn from our trials and mistakes.
- We are easy to work with: we want our workplace to be one where everyone can share their perspective and be treated with respect and kindness.
