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Compound Logistics Workflow and Integration Scientist

roche · Basel

Nouveau
Mid 🇬🇧 English
Python SQL Relational databases GitHub Copilot Claude Code

Description du poste

About the role

In the Small Molecule Research department (SMR) of Pharma Research and Early Development, the CLEL team supplies research samples for SMR projects and holds the Roche Corporate Compound Collection. Using automation platforms and digital workflows, it enables drug discovery with timely delivery of samples for biological assays. Roche is seeking an analytical scientist in its Basel Innovation Center to help explore and implement next-generation end-to-end sample logistics workflows, building workflow engines that track, plan and securely connect decisions across the automated IT infrastructure.

Key responsibilities

  • Scope, design and engineer an interconnected workflow engine that maps, tracks and captures decisions and data across automated business processes.
  • Develop solutions that lower technical barriers for sample, data and information transfer and for decision-making between internal and external stakeholder-facing systems.
  • Support compliance workflows for sample and data management, and overhaul automated compound QC workflows toward AI-assisted data analysis pipelines.
  • Partner with automation engineers and lab staff to build business dashboards and track KPIs and interface effectiveness.
  • Shape the transition to AI-based software development: build and maintain tools with AI coding assistants and set review, testing and documentation practices.
  • Design and implement agentic workflows where AI agents carry out multi-step tasks such as data analysis and issue diagnosis, with human oversight.
  • Act as expert point of contact for operational workflows and contribute to the architecture of future tools.

Required profile

  • University degree, preferably M.S. or B.S. in computer science, cheminformatics, a life science or another scientific discipline with a strong computational focus, or equivalent practical experience in laboratory automation and research informatics.
  • Solid experience in business analysis, process mapping or operations engineering in a pharma or biotech research facility.
  • Familiarity with laboratory information flows, sample management logistics and automated compound QC workflows.
  • Comfortable owning software-based solutions and collaborating with experts, vendors and IT partners in a matrix environment; good English presentation and communication skills.

Required skills

  • Python, SQL and relational databases, version-controlled codebases, testing, deployment and operation in server-based environments.
  • Hands-on experience with agentic AI tools such as Claude Code and GitHub Copilot.

Questions fréquentes

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Source : ats:workday

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roche

Basel