Senior Bioinformatics Scientist

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. We are building a new assay modality on our platform, and its success depends on tight iteration between the bench and the data. In this role, you will own the analysis side of this effort end to end: partnering daily with experimentalists to troubleshoot and optimize protocols, analyzing every type of data the platform produces, explaining what the results mean, and recommending what to try next. You will also build the pipeline for this new data type and work with R&D leadership to frame findings. We are looking for an applied, hands-on scientist who gets things done – someone who values progress over perfection, isn't afraid to dive into unfamiliar territory, knocks down barriers without waiting to be asked, and is a partner the experimental team looks forward to working with.

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 side by side with experimentalists to develop and optimize a new assay format, including designing experiments, selecting which conditions to vary, defining the metrics that determine success, and recommending a path forward based on the results.

Troubleshoot protocols by forming and testing hypotheses that span sample preparation, reagents, fluidics, imaging, and data processing.

Analyze and integrate data across every modality the platform produces, including images, fluidics readouts, fluorescence signals, and decoded single-molecule outputs.

Own the interpretation of results – what the data mean, how confident we should be, and what to do next – and work with R&D leadership to frame findings, communicate progress & risks, and inform project direction.

Design and build a durable analysis pipeline, quality control metrics, and dashboards for this new data type, balancing rapid one-off analyses with tested, reusable tools the broader team can run.

Work with the bioinformatics team to develop new analytical and statistical approaches for interpreting stochastic single-molecule measurements.

Quickly learn to locate and access assay data wherever it lives, including cloud databases, object storage, on-premises file servers, and raw instrument output, writing code to parse instrument metadata and managing cloud access as needed.

Requirements

A PhD in Bioinformatics, Computational Biology, Biophysics, Biochemistry, Biostatistics, or a related quantitative field.

A minimum of 4 years of experience in industry.

A track record as an applied, hands-on scientist who gets things done: comfortable making progress with imperfect information, diving into unfamiliar territory, and removing obstacles.

Hands-on experience analyzing data from wet-lab experiments, with a demonstrated record of assay development or optimization in close partnership with experimental teams.

Demonstrated ability to own a project end to end, from experimental design and analysis through interpretation and recommendations.

Exceptional written and verbal communication skills, including the ability to frame results for leadership and explain technical findings to non-computational audiences.

Solid foundation in applied statistics, including distributions & variability, hypothesis testing, and experimental design.

Proficient in Python (e.g., pandas, NumPy, SciPy) and SQL, with experience building both durable pipelines & dashboards and rapid one-off analyses.

Comfortable working across local machines, shared servers, and cloud environments (e.g., AWS), including Linux, Git, and managing access credentials.

Ability to contribute on an organized and dynamic team in a fast-paced environment.

Hands-on wet-lab experience strongly preferred.

Experience with proteomics, fluorescence imaging, single-molecule methods, instrument development, or affinity reagents preferred.

Experience with probabilistic modeling of stochastic data or protein structural modeling 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 & 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.