Data Engineer

Company: Nomic Bio Founded: 2017 Batch: W20 Team Size: 24 Status: Active Location: Montreal, Canada (Headquarters) with a satellite research lab in Boston, Massachusetts Nomic was founded with the purpose of making biology easier to measure. To do this, we have untangled some of the most difficult problems in protein profiling. Our team is combining DNA nanotechnology, high-dimensional flow cytometry, laboratory automation, and machine learning to develop the world’s highest throughput proteomic platform: the nELISA. Since spinning out of McGill University, we have partnered with and provided platform access to dozens of drug discovery groups including GSK, 4 of the top 10 pharmas, and leading biotechs. We have recently launched a state of the art manufacturing and protein profiling facility that enables multiplexed measurement of >2.5M samples a year, generating an effective 500M protein assays in the process. We are building a diverse team of engineers, scientists, and world-changers. We like to break down difficult problems using a first principles approach, often leveraging the latest breakthroughs from across the scientific and technological spectrum to drive our mission forward. Nomic is headquartered in Montreal, Canada with a satellite research lab in Boston, Massachusetts. The majority of our team is based in Montreal and works in a new, shared office/laboratory space with an in-person but flexible work-from-home policy.

About the role:

Our Data team’s mission is to build, operate and maintain the data infrastructure and data pipelines needed for analyzing nELISA data at scale. Strong fundamentals in data science and data engineering is key to our vision of the future...

Responsibilities:

• Design, build, improve, automate, deploy and scale data pipelines for processing flow cytometry data into quantitative protein measurements.
• Design and implement data platform architecture including data lakes.
• Build and maintain ETL pipelines ensuring data quality...
• Develop internal tooling to support company growth.
• Communicate effectively within cross-functional teams...
• Analyze nELISA data using decoding tools; develop new pipelines leveraging technical expertise.
• Support R&D and Lab Operations teams with experimental design guidance.

Qualifications:

• 4+ years industry experience building data or machine learning pipelines for bioscience data or equivalent academic proficiency.
• 2+ years software engineering/development experience.
• Strong engineering or applied sciences background or related technical field.
• Statistical skills including Bayesian statistics...
• Proficient in modern biotechnology tools/methods such as sequencing...
• Working knowledge of surface chemistry...
• Experience collaborating with wet lab scientists preferred.
• Excellent communication skills (written/verbal/codebase).
• Experience interfacing with LIMS/QC/QMS systems.

Location:

Remote (United States) / Remote (US)

Employment Type:

Full-time

Remote Work Info:

Position is remote within United States.