AI-Driven Lab Data Architect for Assay Workflows

Try&Hire; Basel; On-site; CHF 120,000 - 180,000; Full time

Job summary

Try&Hire is seeking a highly qualified data and AI workflow architect in Basel to design data pipelines and agentic AI workflows that connect laboratory instruments to FAIR-compliant data systems in a pharmaceutical research setting.

You will lead rollout, training, and onboarding for assay development, screening LIMS, and associated data trails, while accelerating assay design and reducing errors through integrated DOE frameworks and ML/LLM API tools.

Qualifications

• PhD or MS in Computational Biology, Scientific Informatics, Bioinformatics or related quantitative discipline.
• Experience with cellular, biochemical or biophysical systems.
• Familiarity with FAIR data management standards.
• Experience with laboratory informatics environments such as LIMS or electronic lab notebooks.
• Strong programming proficiency including database building and ML/LLM API integration.
• Collaborative communicator able to train cross-functional users.

Responsibilities

• Lead rollout and training for assay development and screening LIMS with traceable data trails.
• Design and integrate agentic AI tools and Design of Experiments frameworks.
• Build pipelines connecting raw instrument outputs to databases for FAIR data standards.
• Coordinate user onboarding and train bench scientists on platform adoption.
• Accelerate assay design and execution times and reduce processing error rates.

Skills

Data pipeline design

AI tool integration

Database design

Cross-functional training

Education

PhD/MS in Computational Biology or related

Tools

LIMS

Electronic lab notebooks

Databases

Job description

Try&Hire is seeking a highly qualified data and AI workflow architect in Basel to design data pipelines and agentic AI workflows that connect laboratory instruments to FAIR-compliant data systems in a pharmaceutical research setting.

You will lead rollout, training, and onboarding for assay development, screening LIMS, and associated data trails, while accelerating assay design and reducing errors through integrated DOE frameworks and ML/LLM API tools.