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TetraScience

Cloud-native platform centralizing scientific data

Scientific Data Architect

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeBasel, Switzerland

About the Job

Requirements

  • PhD with more than 4 years or Master's with more than 8 years of industry experience in life sciences, with extensive domain knowledge in drug discovery (target identification through lead optimization), preclinical development, chemistry, manufacturing and controls (CMC) across all drug modalities, or product quality testing.
  • Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments.
  • Experience collaborating with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
  • Experience performing exploratory data analysis and workflow optimization to enable new scientific outcomes.
  • Ability to engage audiences ranging from scientists to executive stakeholders through communication and storytelling.
  • Experience advising scientists in a consulting capacity to further research, development, and quality-testing outcomes.

Responsibilities

  • Engage directly with customers onsite in the Basel region a couple of days per week, building relationships, understanding scientific data challenges and requirements, and accelerating solutions.
  • Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and adaptability.
  • Translate scientific data workflows into solutions leveraging the Tetra Data Platform.
  • Own, scope, prototype, and implement solutions, including data model design (tabular and JSON), Python-based parser development, lab software (such as ELN/LIMS) integration via APIs, and data visualization and app development in Python using frameworks such as Streamlit and plotting tools such as holoviews and Plotly.
  • Collaborate with Scientific Business Analysts, customer scientists, and applied AI engineers to develop and deploy machine learning, artificial intelligence, mechanistic, statistical, and hybrid models.
  • Programmatically interrogate proprietary instrument output files.
  • Iterate with scientific end users and technical stakeholders through regular demos and meetings to drive solution development and adoption.
  • Communicate implementation progress and deliver demos to customer stakeholders.
  • Collaborate with the product team to build and prioritize the roadmap by understanding customers’ pain points within and outside the Tetra Data Platform.
  • Learn new technologies, such as AWS services or scientific analysis applications, to develop and troubleshoot use cases.

About the Company

TetraScience

Cloud-native platform centralizing scientific data

TetraScience offers a cloud-based Scientific Data Cloud that helps biopharmaceutical teams collect, centralize, and harmonize scientific data from lab instruments, software, and apps. It connects data across R&D, QA/QC, and manufacturing so data workflows run faster and data is ready for AI/ML analyses. The platform is vendor-neutral and open, designed to work with any lab equipment or software, providing end-to-end data management across the biopharma value chain. Its goal is to improve scientific outcomes by turning scattered data into a unified, ready-to-use data foundation that accelerates data-driven discovery and production.

Company size
201-500
Company stage
Series B
Total funding
$117.2M
Headquarters
Boston, MA
Founded
2019

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