Compound Logistics Workflow and Integration Scientist
Roche is hiring a Compound Logistics Workflow and Integration Scientist in Basel, Switzerland. Level rates it ; you can apply on Roche.
Level's read on this job
- Level rates this role Uses AI ●●○○: an ordinary role that requires AI tools.
- The posting mentions Claude, Copilot and Claude Code among its tools and skills.
- Roche has 1,200+ other open roles on Level.
- Posted in the last few days.
AI in this role
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
The Position
At Roche, we believe it’s urgent to deliver medical solutions right now – even as we develop innovations for the future. We are passionate about transforming patients’ lives and we are fearless in both decision and action. And we believe that good business means a better world. That is why we come to work each day. We commit ourselves to scientific rigor, unassailable ethics, and access to medical innovations for all. We do this today to build a better tomorrow.
In the Small Molecule Research department (SMR) in Pharma Research and Early Development (pRED), we generate molecular insights, and drive the discovery and development of small molecules from initial starting points to clinical candidates across the pRED discovery portfolio. In the Compound Library Enhancement and Logistics (CLEL) team, we supply research samples for all SMR portfolio projects and serve as the custodians of the Roche Corporate Compound Collection. Using state-of-the-art automation platforms and digital workflows, our mission is to enable drug discovery projects with the supply of proprietary chemical space and the timely delivery of research samples that can be subjected to biological assays.
As the CLEL team is spearheading novel digital processes and AI-augmented drug discovery workflows, we are seeking an analytical and forward-thinking scientist to join our team in the Roche Innovation Center Basel and contribute to the exploration and implementation of next-generation end-to-end sample logistics workflows.
The position:
In this role, you will focus on building the next-generation workflow engines that track, plan, and securely connect decisions across our entire automated IT infrastructure. You will serve as a key business analyst, modernizing legacy systems, eliminating static steps, and replacing them with fully automated, FAIR-compliant, interoperable workflows and data foundations built for scalable automation and AI that keep the drug discovery path moving at maximum velocity.
This role will deliver efficiency gains by lowering business process overhead and improve coordination. It will also increase visibility and develop new planning capabilities leading to better decisions on investments and strategic resource planning, resulting in streamlined sample delivery and data processes.
Specifically, you will:
- Scope, design and engineer an interconnected next-generation business workflow engine capable of mapping, tracking, and capturing decisions and data across automated business processes.
- Develop solutions to lower technical barriers for sample, data and information transfer, as well as decision-making at the interface of internal or external stakeholder-facing systems.
- Support compliance workflows in sample and data management (i.e. sample decisions, documentation), as well as overhaul automated compound QC workflows towards AI-assisted data analysis pipelines.
- Partner with automation engineers and laboratory staff to generate business dashboards and track key performance indicators (KPIs) and interface effectiveness to key stakeholders.
- Shape and drive our ongoing transition to AI-based software development: build and maintain tools together with AI coding assistants, and establish the practices (review, testing, documentation) that keep AI-generated solutions reliable and future-oriented.
- Design and implement agentic workflows in which AI agents carry out multi-step tasks such as data analysis, issue diagnosis and routine operations, with clear human oversight and safeguards for operational systems and data.
- Act as expert point of contact for operational workflows: shape the evolution of our system landscape, develop solutions with emerging AI technologies, and contribute to the architecture of future tools.
Who you are:
You’re someone who wants to influence your own development. You’re looking to be part of a dynamic and cutting-edge organization where you have the opportunity to pursue your interests across functions and tasks. You are interested in making an impact by providing solutions, reducing complexity and connecting essential elements of the drug discovery process and are passionate about applying state-of-the-art technology and science to the biopharmaceutical industry.
- You have a university degree, preferably an M.S. or B.S. in computer science, cheminformatics, a life science or another scientific discipline with a strong computational focus, or show equivalent practical experience and expertise in laboratory automation and research informatics.
- You have exceptionally structured thinking and problem-solving skills, with the ability to bridge physical logistics with software logic. You can also translate complex thoughts into practical, robust, applications and solutions.
- You have a solid experience in Business Analysis (BA), process mapping, or operations engineering, specifically within a pharmaceutical or biotechnology research facility.
- You must be familiar with laboratory information flows, sample management logistics, and automated compound QC workflows.
- You are comfortable working with and taking ownership of software-based solutions, from Python, SQL and relational databases to version-controlled codebases, testing, deployment and operation in server-based environments.
- You have hands-on experience with agentic AI tools (e.g. Claude Code, GitHub Copilot) used for real work beyond chat: handing over multi-step tasks, giving AI agents the right context, and critically verifying what they produce.
- You have strong interpersonal skills to influence, advise and collaborate with experts, vendors and IT partners in a matrix environment to jointly move projects forward.
- Your profile is rounded off by having good presentation and communication skills in English.
The scientific title of this position might be adjusted depending on the experience and seniority of the final candidate.
If you are proud of contributing and feel you have the dedication to teamwork and innovation that we are seeking, then Roche is the organization for you. Every role at Roche plays a part in making a difference to patients’ lives. If you want to work in a passionate team, make your mark and improve lives, apply now.
Who we are
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
Roche is an Equal Opportunity Employer.
How we rate this
Compound Logistics Workflow and Integration Scientist at Roche rates 44 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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