Scientific Data Engineer

Who We Are

TetraScience is the Scientific Data and AI company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes.

TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships : Latest News and Announcements | TetraScience Newsroom

In connection with your candidacy, you will be asked to carefully review the Tetra Way letter , authored directly by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective.

It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day.

What You Will Do

• Research data acquisition strategy for scientific lab instrumentation
• Research and productionize file parsers for instrument output files (.xlsx, .pdf, .txt, .raw, .fid, many other vendor binaries)
• Design and build data models and the corresponding data pipelines, unit tests, integration tests, and reusable utility functions
• Cross-analyze instrument data with the same instrument type or scientific workflow to design common data model components.
• Build visualization, report, and dashboards using Streamlit, Tableau, Jupyter notebook, etc.
• Drive value for the customers - test and make sure the solution fulfills their requirements and provides value

What You Have Done

5 years experience in Python and SQL

3 years of work experience in pharmaceutical or biotech industry in scientific data engineering, data modeling, or data analytics.