Nomic Bio

Data Analyst

• Finalizing nELISA data reports
• Creating visualizations for data
• Ensuring the seamless delivery of projects to Nomic customers
• Regular customer interactions and meetings
• Supporting customers during onboarding and addressing ongoing questions
• Gaining insights into customers’ research questions and relaying to product team

Customer Success Data Analyst

Full-stack Engineer

• Build core sub-components of our software stack — database schemas, analysis pipelines and new analysis algorithms, cloud infrastructure and related IaC, full-stack web interfaces, machine learning models, and APIs consumed by our own services and by customers. You'll lean on AI coding tools to move quickly, while owning the architecture, review, and correctness.
• Design and build agentic backends, skills, and AI-augmented tooling — including LLM-powered workflows and machine-readable interfaces — that let our teams (and our agents) interact safely with the LIMS, data pipelines, and lab automation. Help us figure out where agents create real leverage and where they don't.
• Develop improved internal tools for our LIMS, and software for our R&D teams, in order to increase operations and R&D velocity in the lab, including developing and implementing an electronic lab notebooks (ELN) plan tailor fit to our profiling and manufacturing lab operations.
• Write modular software that we can use to create efficient analysis pipelines and internal QC tools, making use of existing libraries, open source platforms, and commercial options as best suited to the challenges at hand.
• Build better interfaces to the tools that are available out-of-the-box from our robotic lab automation equipment suppliers, and extend these capabilities going forward so as to enable our lab teams to interface with our software stack as seamlessly as possible.
• Contribute improvements to the codebase that enable us to further scale up our nELISA decoding and analysis pipelines; write tests and evals, including for AI-generated code and ML/agentic components, integrate the stack with appropriate monitoring and analytics, and set up robust CI/CD when appropriate.
• Deploy and scale our data pipelines for processing flow cytometry data into quantitative protein concentrations. This will be done in close collaboration between our Data Engineering and Software Engineering teams.
• This role will involve substantial communication and teamwork not just within our software engineering team at Nomic, but also with the broader range of internal users of the LIMS, data portal, and data pipeline software, including customers at times.

Customer Success Data Analyst

Software Engineer – Mid to Sr Levels