AI-Driven Scientific Data Architect - Remote

TetraScience

Basel

Hybrid

CHF 85.000 - 170.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden
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Benefits dieser Stelle

Competitive salary
Equity
PTO
Remote work

Zusammenfassung

TetraScience is seeking a product-minded biopharma AI lead who will co-create and industrialise Scientific AI solutions for customers in the Frankfurt region, with on-site work a couple of days weekly. You will design scalable data models, translate scientific workflows, and build Python-based parsers and lab software integrations.

You will collaborate with scientists, PMs, engineers and SBAs to deploy ML/AI models, learn new tools rapidly, and help prioritise the roadmap while maintaining

Qualifikationen

  • PhD (with 4+ years) or Master (with 8+ years) in life sciences.
  • Proven track record defining and prototyping AI/ML use cases in the cloud.
  • Experience collaborating with scientists, PMs, engineers and stakeholders.

Aufgaben

  • Industrialise Scientific AI in a unique customer-facing partnership.
  • Design extensible data models to capture scientific data for use cases.
  • Translate workflows into robust solutions on the Tetra Data Platform.
  • Prototype and implement data models, Python parsers and lab software integrations.
  • Collaborate with SBAs, scientists and AI engineers to deploy models.

Kenntnisse

PhD +4 years in life sciences
Masters +8 years in life sciences
AI/ML in cloud
German language (C1)
Cross-functional collaboration

Ausbildung

PhD in life sciences
Masters in life sciences

Tools

Python
Streamlit
Plotly
Holoviews
ELN/LIMS APIs

Jobbeschreibung

TetraScience is seeking a product-minded biopharma AI lead who will co-create and industrialise Scientific AI solutions for customers in the Frankfurt region, with on-site work a couple of days weekly. You will design scalable data models, translate scientific workflows, and build Python-based parsers and lab software integrations.

You will collaborate with scientists, PMs, engineers and SBAs to deploy ML/AI models, learn new tools rapidly, and help prioritise the roadmap while maintaining

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