About the role

Senior position focusing on data pipelines and bioscience data analysis for an innovative biotechnology firm. Collaborate across teams to drive data-based advancements.

Responsibilities

Designing, building, iteratively improving, and fully automating the data pipelines and algorithms we use for processing raw flow cytometry data from our highly multiplexed bead-based assays into quantitative protein measurements.
You will leverage your fundamental knowledge of biosensors, fluorescence data, and bioengineering R&D to act as an expert for the interpretation, and analysis of, nELISA experimental data when challenges arise in R&D and day-to-day Lab Operations.
You will also support R&D and Lab Operations teams through developing additional data support features and algorithms to support the growth of Nomic going forward.
This role will involve substantial communication, teamwork, and attention to detail, especially when identifying and troubleshooting issues related to nELISA data and ensuring we build the right tools, and the right abstractions.
When tooling does not yet exist, you will leveraging your technical and bioscience domain expertise to develop new data analysis pipelines.

Graduate Degree - or equivalent experience in industry - in bioengineering or a related quantitative field of study in the biosciences, with a focus on biosensors, quantitative fluorescence data, or similar.
3+ years of experience specifically with analyzing bioscience data and developing improved data processing algorithms.
2+ years software engineering/development experience - you must be comfortable standing up new toolsets for non-programming users, and coding in a collaborative environment together with experienced data and software engineers.
Statistical skills including bayesian statistics, sampling methods, mixed models, and experience applying other statistical concepts.
Strong past experience working collaboratively on data science problems with wet lab scientists, ideally in a startup or equivalent fast paced environment.
Nice to Have: Understanding of the fundamentals of life science tools, technologies and lab methods.
Nice to Have: First hand experience optimizing (alone or in a team): surface chemistry, DNA-based circuits and DNA biosensor designs, fluorophores/fluorescence and FRET, antibody-antigen interactions and ligand binding, or similar domains.
Excellent communication skills (written, verbal, and in a codebase) and an independent problem solver.
Fluency in English is required.