Sr Scientist, Lab Informatics (temp role)

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com . As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Discovery & Pre-Clinical/Clinical Development Job Sub Function: Pharmaceutical Product R&D Job Category: Scientific/Technology All Job Posting Locations: Beerse, Antwerp, Belgium Job Description: Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at https://www.jnj.com/innovative-medicine Join us as a lab informatician and help build the next generation of digital and agentic capabilities for Synthetic Molecule Analytical Development. You will contribute as an agentic AD developer within one focused analytical program . Your impact will come from building useful, working capabilities close to the scientific work, in collaboration with analytical domain experts, a domain leader, key users, and digital partners. We are looking for someone who can sit close to the science and close to the code. The ideal candidate does not need to be the most senior developer in the room. The stronger fit is someone with enough technical skill to build, enough scientific curiosity to understand the problem, and enough pragmatism to deliver something useful with real users. This person should like working in small, focused teams where the developer, domain leader and key user stay close together. In this model, the developer builds fast, the domain leader owns the scientific intent and acceptance criteria, and the key user tests whether the solution works in real analytical practice. The ambition is to move towards reusable analytical co-scientist capabilities that support product understanding, method development, evidence generation, and CMC decision-making. We will get there by building small, meaningful capabilities, learning from real use, and improving the roadmap through evidence rather than assumptions. This role sits in the Technology and Transformation Alliances team and will contribute directly to the future of Analytical Development by combining lab informatics, data, coding, and scientific domain understanding. Primary responsibilities: Develop and maintain focused digital solutions, prototypes, and agentic workflows using Python and relevant application frameworks. Translate analytical use cases into practical data workflows, user interfaces, scripts, and reusable components. Work closely with an experienced domain leader and hands-on key users to understand scientific intent, acceptance criteria, and real workflow needs. Collaborate with digital/data partners to align with existing platforms, enterprise tools, coding practices, and reusable architecture. Build small increments that can be tested quickly, improved through feedback, and scaled only when they demonstrate value. Help connect available analytical data sources where appropriate, while clearly identifying missing data, quality gaps, and workflow constraints. Support development of capabilities such as data retrieval, evidence structuring, quality checks, comparison logic, reporting drafts, recommendation support, or workflow automation. Document your work clearly so that capabilities can be understood, maintained, and reused by others. Support troubleshooting, refinement, and basic lifecycle maintenance of the solutions you build. Contribute to a learning-oriented, agile way of working where the first goal is useful capability development, not perfect architecture. Qualifications Education: Master’s degree or equivalent experience in a relevant field such as bioengineering, chemistry, pharmaceutical sciences, computer science, data science, engineering, statistics, or a related discipline. A PhD is not required. Required: Early-career professional with relevant experience or strong demonstrated capability in lab informatics, scientific computing, data science, automation, or software development. Practical programming experience in Python. Interest in analytical development, lab workflows, scientific data, and pharmaceutical R&D. Ability to translate a scientific or workflow problem into a practical digital solution. Willingness to work iteratively, test with users, and improve based on feedback. Basic understanding of data handling, APIs, databases, notebooks, dashboards, or web applications. Strong collaboration skills and ability to work with scientists, IT/digital partners, and domain experts. Clear communication style, including the ability to document assumptions, limitations, and next steps. Curiosity, ownership, and willingness to learn both the technical and analytical domain. Preferred: Experience or affinity with analytical development labs, chromatography, LC/MS, dissolution, stability, PAT, laboratory automation, ELN, LIMS, CDS, or related workflows. Experience with Python frameworks such as Flask, FastAPI, Django, Dash, Streamlit, or similar. Experience with JavaScript, TypeScript, React, or other front-end tools. Familiarity with AI/ML, LLM-based workflows, retrieval-augmented generation, agents, or scientific decision-support tools. Experience working in a regulated or quality-sensitive environment. Familiarity with cloud, containers, Git, CI/CD, or enterprise software development practices. Ability to work with imperfect data and still deliver useful, transparent, scientifically grounded outputs. Working conditions You will work on one analytical co-scientist or agentic capability lane, selected based on your strengths, scientific affinity, and the needs of the program. This could include areas such as LC and impurity evidence, stability evidence, dissolut