Senior Scientist, DSCS Digital Technologies-Laboratory Automation, Scientific Data Integration (Hybr

Job Description In the Development Sciences and Clinical Supply (DSCS) organization, we believe digital is the force multiplier that enables faster experiments, smarter decisions, more robust supply chains, and is ultimately redefining how we bring medicines to patients. Within Development Sciences and Clinical Supply, the Development Sciences and Clinical Supply Digital Technologies team is building the next generation of data-rich, connected lab environments- where hardware, software, and AI-driven tools work together to accelerate pharmaceutical development. Our goal is simple but ambitious: embed advanced digital capabilities into the DNA of how we work. We believe this future starts with a strong foundation of laboratory tools: innovative robotics, process analytical technology, high-throughput technologies, reliable instrumentation, and integrated systems that seamlessly contextualize data and transition it from the physical labs to the digital world. Our innovation is fueled by teams coming together to build technologies that truly impact how our scientists conduct research. We're looking for a Senior Scientist to help realize this vision. In this role, the chosen candidate will work with a team of scientists tasked with identifying, developing, and deploying digital and data-rich technologies aimed at improving Process, Product, and Analytical understanding. The tools that we develop are as the team developing them, and in this role, the chosen candidate will leverage digital technologies to enable chemistry, manufacturing, and controls activities across our small molecule, biologics, and vaccines portfolio. Working at the intersection of pharmaceutical science, digital technologies, and data integration, the candidate will help enable FAIR, AI-ready scientific data ecosystems that accelerate research, enhance decision making, and improve the way scientific knowledge is generated, managed, and reused across the development lifecycle. In this role, the candidate will help us progress towards our goal of automated and connected laboratories. The candidate will leverage industry standard and emerging technologies to enable integration, orchestration, and visualization of laboratory systems and workflows. This position will work collaboratively across laboratory automation, digital engineering, and IT teams to independently own and deliver technical solutions connecting laboratory equipment, automation systems, and data pipelines into cohesive, scalable solutions aligned with our future vision. How You'll Make an Impact Connect the ecosystem by integrating instrument and equipment platforms with semantic context and data systems to enable end-to-end digital workflows Work at the intersection of disciplines , collaborating with experts in automation, data science, modeling, IT, knowledge capture, and the chemistry, manufacturing, and controls community at large Translate science into systems by partnering with researchers to understand experimental needs and integrate them with scalable digital workflows Lead high-impact projects from concept through deployment, working across teams and stakeholders to deliver meaningful outcomes Design the lab of the future by developing automation systems that integrate robotics, instrumentation, equipment, and software into cohesive, high-performing solutions Continuously improve existing automation platforms to enhance performance, usability, and reliability Empower others by providing hands‑on partnership, support, troubleshooting, and training to scientists using these technologies Education Minimum Requirement A Ph.D. in Chemistry, Biochemistry, Engineering (i.e., Mechanical, Electrical, Chemical), Physics, Biology, Pharmaceutical Sciences, Computer Science, Data Science, Material Science or a closely related field (with expected graduation no later than December 2026). A M.S. in Chemistry, Biochemistry, Engineering (i.e., Mechanical, Electrical, Chemical), Physics, Biology, Pharmaceutical Sciences, Computer Science, Data Science, Material Science or a closely related field with at least 2 years of relevant experience A B.S. in Chemistry, Biochemistry, Engineering (i.e., Mechanical, Electrical, Chemical), Physics, Biology, Pharmaceutical Sciences, Computer Science, Data Science, Material Science or a closely related field with at least 4 years of relevant experience Required Experience and Skills Proficient in Python and/or R programming. Comfortable working in development environments such as Jupyter, Posit/RStudio, or VS Code. Experience with ETL/ELT processes and building data pipelines in a scientific or pharmaceutical context. Familiarity with version control systems (Git/GitHub) and collaborative software development practices. Understanding of (bio)pharmaceutical process research and development, drug product development, and/or analytical development Excellent communication skills, demonstrated creativity, and effective interpersonal skills Ability to deliver complex solutions under compressed timelines in a dynamic environment Ability to work in a team environment with cross‑functional interactions Demonstrated ability to work in an entrepreneurial and independent manner on cross‑functional teams Demonstrated scientific ability through publications and presentations in scientific conferences Preferred Experience and Skills Understanding of knowledge representation and reasoning techniques. Working knowledge of ontology design, FAIR principles, data/metadata standards, and scientific data management practices Understanding of semantic modeling, knowledge representation, and scientific data contextualization approaches Familiarity with life‑science data standards, including Allotrope, CDISC, or comparable frameworks Experience working with heterogeneous scientific data sources and integrating information across multiple systems or domains Experience connecting heterogeneous data sources and resolving differences in terminology, structure, and quality Ability to model concepts, entities, relationships, and rules in a machine‑readable way Familiarity with ontology frameworks or standardized data models (e.g., Allotrope Simple Model, ISA-88, OPC-UA) and experience mapping instrument data to structured schemas. Understanding of data science and AI/ML concepts and their application to data contextualization Background in leveraging a broad range of data engineering and data science technologies, including digital integration of analytical instrumentation Wet lab experience in (bio)pharmaceutical drug substance, drug product, and analytical research and development Motivated to learn new skills, willingness to take on new challenges, and scientific curiosity EligibleforERP Required Skills Analytical Instrumentation, Bioprocessing, Chemistry, Data Engineering, Data Pipelines, Data Science, High-Throughput Screening, Innovative Thinking, Laboratory Automation, Ontology, Pharmaceutical Process Development, Python (Programming Language), Robotics, Scientific Data #J-18808-Ljbffr Merck & Co.