10 months ago
Remote, United StatesSenior
Responsibilities
- Design, build, iteratively improve, and fully automate data pipelines and algorithms that process raw flow-cytometry data into quantitative protein measurements.
- Interpret and analyze nELISA experimental data using bioscience, biosensor, fluorescence, and bioengineering expertise.
- Develop data-analysis pipelines, algorithms, support features, and quality-control tools for R&D, manufacturing, and profiling operations.
- Create tools and abstractions that enable scientists and other non-programming users to visualize and analyze datasets more automatically.
- Troubleshoot nELISA data issues and support experimental design and analysis in collaboration with laboratory R&D and operations teams.
- Collaborate cross-functionally with data engineering, software engineering, laboratory R&D, operations, and commercial teams.
Requirements
- Graduate degree in bioengineering or a related quantitative bioscience field, or equivalent industry experience, with a focus on biosensors, quantitative fluorescence data, or a similar area.
- At least 3 years of experience analyzing bioscience data and developing improved data-processing algorithms.
- At least 2 years of software engineering or development experience, including building tools for non-programming users.
- Statistical skills involving Bayesian statistics, sampling methods, mixed models, and related statistical concepts.
- Experience collaborating on data science problems with wet-lab scientists, preferably in a startup or similarly fast-paced environment.
- Preferred experience with life-science tools and methods such as immunoassays, nucleic-acid amplification, DNA nanoarchitecture and design, biological separation techniques, biophysics, fluorescence, and signal processing.
- Preferred hands-on experience optimizing surface chemistry, DNA-based circuits or biosensors, fluorophores or fluorescence, FRET, antibody-antigen interactions, ligand binding, or similar domains.
- Strong written, verbal, and codebase communication skills and independent problem-solving ability.
- Fluency in English is required.
Categories
Data EngineeringData Science
About nomic
Nomic builds a proteomics measurement platform based on its nELISA technology and offers end-to-end services and kits that generate large-scale, quantitative protein data for drug discovery and biomarker development. It sells assays run in-house or on customers’ commercial flow cytometers, serving pharma, biotech, and academic labs; partners have included GlaxoSmithKline and the Broad Institute. Founded in 2017 and headquartered in Montreal, it also operates a Boston research site.