Scientific Business Analyst

Who We Are

Tetra Science 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.

Tetra Science 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 Tetra Science as the de facto standard, entering into co-innovation and go-to-market partnerships:
Latest News and Announcements | Tetra Science 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 Tetra Science 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 are a strategic, analytically minded professional with a passion for bridging scientific insights and cutting-edge technology. You thrive in environments where you can collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes.

With deep domain knowledge in drug discovery/preclinical development, CMC, or Quality, you are skilled at uncovering innovative use cases that drive AI and machine learning applications. 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 a high clock speed and forward-thinking individual with a passion for developing requirements for complex solutions targeted to R&D and Quality personas inside of Life Sciences.

You will need to be a high clock-speed, forward-thinking individual with a passion for developing requirements for complex solutions targeted to R&D and Quality personas inside Life Sciences. 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.

You should also be energized by regularly working onsite with customers
. You thrive in dynamic, high-impact, face-to-face collaborative environments where you can build deep relationships and drive scientific transformation firsthand.

• PhD with 15+ 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 AI/ML-driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization.
• Extensive hands-on experience with scientific data workflows and lab automation; exposure to FAIR principles and modern data architecture is a plus.
• Strong coding or scripting background (e.g., Python, Nextflow, AWS, SDKs) and familiarity with scientific tools, databases, and ontologies is preferred.
• Exceptional communication and storytelling ability to engage technical and executive stakeholders.
• Prior experience in customer-facing, consulting, or commercial-scientific interface roles.

• You will be a critical team member in a unique partnership to industrialize Scientific AI. As such, you will engage directly with customers onsite up to 4-5 days per week in the Basel Region
• Customer Data Exploration
  :
  Investigate diverse customer datasets, identifying enrichment and AI-readiness opportunities.
• Scientific Use Case Development: Co…