WHO WE ARE

TetraScience is the Scientific Data and AI Cloud 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 HAVE DONE

• PhD with 15+ years of industry experience in life sciences with extensive domain knowledge in drug discovery (target ID through lead optimization), preclinical development, CMC (all drug modalities), or product quality testing.
• Proven track record of defining and implementing AI/ML-driven use cases in productized environments.
• Collaborated with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
• Performed extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible.
• Engaged diverse audiences, from scientists to executive stakeholders using your excellent communication and storytelling abilities
• Advised scientists in a consulting capacity to further research, development, and quality testing outcomes.

WHAT YOU WILL DO

• Customer Data Exploration: Investigate customer datasets to identify gaps, enrichment opportunities, and AI-readiness factors.
• Scientific Use Case Development: Collaborate with customers to define, iterate, and refine AI/ML-driven scientific use cases.
• Stakeholder Engagement: Interview scientists and guide them in expanding and leveraging their data for AI applications.
• Data Analysis and Enrichment: Perform exploratory data analysis (EDA) and define data transformations for AI/ML use cases.
• Workflow Documentation: Develop workflow diagrams, process mappings, ERDs, AS-IS/TO-BE workflows, and ontology definitions.
• AI Model Evaluation: Provide feedback on AI/ML models to enhance scientific outcomes and improve product offerings.
• Customer Education and Demonstration: Conduct technical demonstrations, showcase AI applications, and drive adoption.
• Strategic Recommendations: Proactively suggest experiments or data strategies that strengthen customer insights and outcomes.