Sr Data Scientist / Data Engineer

About us

Nomic was founded with a simple but ambitious goal : to make biology easier to measure. Nomic has developed

nELISA , the world’s highest throughput proteomic platform, using DNA nanotechnology, flow cytometry, lab automation, and machine learning. Since spinning out of McGill University, Nomic has partnered with top-tier drug discovery groups, profiled over 60 million proteins from 400,000 samples, and recently scaled up after a $42M Series B round.

Our state‑of‑the‑art facility profiles over 2.5 million samples a year, generating 500 million protein assays. We are a diverse team of engineers, scientists, and problem‑solvers who thrive on first‑principle thinking and the latest breakthroughs.

About the role

The Data team at Nomic designs, builds, operates, and improves the data pipelines, infrastructure, and tools needed to analyze nELISA data at scale. In this senior IC role you will sit at the intersection of in‑lab technology development, data processing algorithms, and manual data analysis, building internal tools that enable scientists to visualize and analyze datasets faster.

Responsibilities

Design, build, iteratively improve, and fully automate pipelines and algorithms that process raw flow cytometry data from high‑multiplexed bead assays into quantitative protein measurements. Collaborate closely with Data Engineering, Software Engineering, and Lab R&D teams.

Leverage your knowledge of biosensors, fluorescence data, and bioengineering R&D to act as a domain expert that ties data science to experimental nuances.

Develop new data support features and algorithms to support growth, including pipelines for nELISA data and QC data from daily manufacturing and profiling operations.

Communicate results, troubleshoot nELISA data issues, and build the right tools and abstractions with attention to detail.

When tooling does not exist, analyze data with existing tools, and develop new pipelines when needed.

Support R&D and Lab Operations with guidance on experimental design and analysis.

Qualifications

Graduate degree or equivalent industry experience in bioengineering or a quantitative bioscience field focusing on biosensors, quantitative fluorescence, or related areas.

3+ years of experience analyzing bioscience data and developing data processing algorithms.

2+ years of software engineering / development experience; comfortable building toolsets for non‑programming users and collaborating in a code‑driven environment.

Strong statistical skills including Bayesian methods, sampling techniques, mixed models, and other advanced concepts.

Experience collaborating with wet‑lab scientists, preferably in a fast‑paced startup or similar setting.

Excellent written and verbal communication, independent problem‑solving, and fluency in English.

Nice to have

Deep familiarity with immunoassays, nucleic‑acid amplification, DNA nanoarchitecture, separation techniques, biophysics / fluorescence, and signal processing.

Experience optimizing surface chemistry, DNA‑based circuits, DNA biosensors, fluorophores / FRET, antibody‑antigen interactions, or similar domains.

What we’re looking for

Connect deeply with our mission and sense of duty.

Embrace challenges and grow within a collaborative, diverse team.

Want to shape the cutting‑edge of biotechnology and design data pipelines that accelerate nELISA scaling.

Love coding and analyzing biological data, driving full‑stack pipeline improvements.

Prefer working in an inclusive environment where your ideas are valued.

Be ready to tackle our hardest problems and help advance the core competency of data.

Additional Information

If you are passionate about building data pipelines for biology and driving innovation in proteomics, we invite you to apply and join us on our journey to redefine proteomics and biology understanding.

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