Jobs at MSD Animal Health Technology Labs

Leads enterprise data science strategy, governance, automation, and analytics enablement across therapeutic areas. Oversees pipelines, data architectures, dashboards, AI/ML adoption, data standards, regulatory compliance, and methodological consistency. Advises executives, partners with clinical and technology teams, manages analytics personnel, drives organizational change, and advances scalable data capabilities. Requires extensive healthcare or life sciences analytics experience, people leadership, and expertise in Python, R, SQL, visualization platforms, clinical data standards, and regulated environments.

Provides advanced administrative support to an Intellectual Property legal group, including document preparation, calendar and schedule management, invoice and budget oversight, travel and expense processing, records maintenance, website and SharePoint updates, visitor coordination, and special projects. Requires strong organization, communication, judgment, confidentiality, multitasking, and proficiency with Microsoft Office and administrative, billing, travel, and intellectual property systems.

Own and prioritize AI and data science product backlogs, translate stakeholder needs into technical requirements, and guide NLP, generative AI, and agentic AI prototypes into reliable production services. Responsibilities include product discovery, roadmap planning, user enablement, adoption measurement, exploratory data analysis, pipeline integration, and model validation. The role collaborates with data scientists, engineers, bioinformaticians, and scientific experts to support drug discovery and development.

Leads development of AI/ML research platforms connecting multimodal data, knowledge graphs, scalable compute, foundation models, and reusable tools. Builds agentic AI frameworks, RAG pipelines, and scientific workflows while overseeing software architecture, testing, CI/CD, reproducibility, security, and maintainability. Partners with scientists and technology teams on cloud, Databricks, GPU, and high-performance computing environments. Remains hands-on in architecture and implementation while mentoring engineers and enabling biomedical research applications.

Leads the enterprise master and reference data product line across Manufacturing, Quality, and Supply Chain. Owns strategy, roadmap, platforms, operating model, data governance, quality, stewardship, ontology management, budgets, vendors, and value realization. Builds and develops a global multidisciplinary organization, drives transformation and adoption, establishes data standards and controls, and applies AI and automation to improve data operations. Partners with senior business and technology stakeholders in a regulated, global environment.