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.
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: 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.
You thrive in environments where you can collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes.
Your ability to engage with scientists and business leaders alike makes you a key player in maximizing the value of scientific data.
You will need to be software-savvy and data fluent with skills to translate scientific workflow to data-related requirements and understand the software implication.
You embody extreme ownership and have a demonstrated history of deriving maximum value from data through enrichment, analysis, and integration with AI and machine learning applications.
PhD with +5 years or Masters with +10 years of industry experience in life sciences, preferably across pharma, biotech, or health tech, with deep domain expertise in discovery, preclinical, CMC, and/or Quality.
Extensive hands-on experience or direct oversight in one or more of the following areas: high throughput screening, preclinical toxicology, materials engineering, analytical development, drug substance (DS) synthesis and manufacturing.
Delivered requirements for data-driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization.
Proven experience and capability to analyze and articulate the business impact of the data-driven solutions via ROI analysis, live presentation, case study.
Exceptional communication and storytelling ability to engage technical and executive stakeholders.
Extensive hands-on experience with scientific data workflows and lab automation; exposure to FAIR principles and modern data architecture is a plus.
Comfortable with basic scripting and data structures, and familiarity with software tools, databases.
Customer Data Exploration : Investigate diverse customer datasets, identifying enrichment and AI-readiness opportunities.
Stakeholder Engagement: Conduct onsite interviews and workshops to deeply understand customer challenges and data landscapes.
Data Analysis and Enrichment: Perform exploratory data analysis and define transformation workflows that enable scientific AI.
Benefits
Competitive Salary and equity in a fast-growing company.
Remote working opportunities, when not at customer sites