Data Analyst

About the company

Nomic is on a mission to make biology easier to measure and to help scientists extend human life by making proteomics more accessible, scalable, and routine. The company began at McGill University, where its founders and early team created a breakthrough approach to protein measurement.

Today, Nomic is built around its proprietary nELISA® platform, an end-to-end system that delivers high-throughput, quantitative, and cost-effective protein data at a scale that was previously out of reach. With Omni 1000, the company is working toward a $50 proteome and removing long-standing barriers in the field. This is opening large-scale quantitative proteomics to more scientists across drug discovery, translational research, and AI-supported therapeutic development.

Nomic has collaborated with organizations across pharma, biotech, and academia, including GlaxoSmithKline and the Broad Institute, and has processed more than 500,000 samples across a range of use cases. The company has raised over $60 million, including a recent $42 million Series B. Headquartered in Montreal, Canada, Nomic also operates a research lab in Boston, Massachusetts.

About the role

The Data team is responsible for creating, maintaining, operating, and improving the data pipelines, infrastructure, and internal tools used to analyze nELISA data at scale. The roadmap includes stronger pipelines for decoding nELISA datasets and better internal tools that help scientists move faster in the lab by accessing insights from profiling and manufacturing QC data on demand.

In this role, you will use Nomic’s data analysis pipelines and tooling to convert raw readout data into quantified proteins for the company’s protein profiling operations. You will help connect customer samples to the profiling lab and ensure that the resulting data is delivered back to customers accurately and efficiently.

You will also be expected to investigate and resolve issues as they arise. That may include fixing bugs in the pipeline or process, spotting signs of sample or process irregularities, and carrying out root-cause analysis for QC failures. The role also leaves room for production data analysts to support broader data engineering work on a regular basis.

An experienced Production Data Analyst can build deep familiarity with Nomic’s workflows through the volume of data processed each day. The role also provides opportunities to strengthen Python skills through troubleshooting and collaboration, creating pathways to future growth within the company.

Key responsibilities

• Use the company’s existing software tools to analyze nELISA data as the core part of the role.
• Investigate data or process issues, including detailed debugging and root-cause assessment.
• Communicate issues clearly and document any follow-up investigation or analysis.
• Spot opportunities to improve workflows and contribute to practical solutions.
• Take part in process optimization and algorithm development efforts.
• Work closely with others and maintain a high level of accuracy when handling nELISA data.

Requirements

• An undergraduate degree in Computer Science, Engineering, Bioengineering, Biology, Applied Biosciences, or a closely related technical discipline.
• Hands-on experience with Python and the scientific Python ecosystem, including numpy, pandas, matplotlib, and Jupyter.
• At least 1 year of experience analyzing data and running bioscience data pipelines in practice, including academic environments.
• Working knowledge of Bayesian statistics, sampling techniques, mixed models, and similar statistical methods, with the ability to turn complex results into clear insights.
• Familiarity with biotechnology tools and methods, ideally with practical experience in at least one area such as sequencing, immunoassays, nucleic acid amplification, DNA nanoarchitecture and design, separation-based methods for biological samples and compounds, biophysics/fluorescence/FRET, or signal processing such as EEG or MRI.
• Strong multitasking ability and exceptional attention to data quality.
• Excellent communication skills, both written and verbal, plus the ability to communicate effectively in code.
• Fluency in English, since customers and vendors are mainly in the USA and the role interacts with team members in the U.S. entity.

Who should apply

Applicants should be motivated by mission-driven biotechnology work, interested in analyzing biological data every day, and eager to help improve data pipelines over time. The role is well suited to people who enjoy close collaboration with cross-functional teams and who want to contribute to the scaling of proteomics technology.

What makes this role appealing

• Work on cutting-edge proteomics and DNA nanotechnology applications.
• Gain deep operational exposure to real production data and data quality challenges.
• Collaborate with R&D, Engineering, Operations, and Commercial teams.
• Build skills in Python, troubleshooting, and algorithmic process improvement.
• Join a diverse, inclusive, and highly collaborative environment where ideas are valued.

Additional information

This position is based in Montreal, Quebec, Canada and is onsite. The role is full-time.

The posting includes both English and French versions of the role details; the French content mirrors the English information and does not add different terms.