Senior Technical Analyst — Chemical Modality Design

Job Description

The Research and Development Sciences (RaDS) value team in our Company's R&D IT brings together product management, engineering, and data science expertise. We enable data, technology, and services that accelerate our scientists’ ability to discover and develop innovative medicines that change the course of human health. In the RaDS value team, the Product organization is responsible for implementing capabilities and associated services to advance the drug discovery and development pipeline. Our IT team operates as a business partner, proposing ideas and innovative solutions that enable new organizational capabilities. We collaborate internationally to deliver the services and solutions that help everyone to be more productive and enable innovation.

The Chemical Modality Design product enables scientists to design and analyze therapeutic molecules through integrated scientific applications, data, computational methods, analytics, artificial intelligence, and machine learning. It supports the Design and Analyze stages of the Design-Make-Test-Analyze cycle across small molecules, peptides, targeted protein degraders, and antibody-drug conjugates.

The Senior Technical Analyst will translate scientific and product needs into technical requirements, solution designs, integration approaches, and implementation plans. The role will coordinate delivery across scientific stakeholders, architects, engineers, internal technology teams, and external software vendors.

The successful candidate will help ensure that scientific solutions are secure, scalable, supportable, and aligned with product and enterprise technology strategies. Experience in cheminformatics, computational chemistry, or scientific informatics, along with the design and implementation of analytics, machine learning, or agentic capabilities within scientific workflows using AI-assisted tools is strongly preferred.

What will you do?

• Translate scientific workflows and product needs into technical requirements, user stories, acceptance criteria, system interactions, and data flows.
• Lead technical analysis for new capabilities, integrations, application upgrades, and modernization initiatives.
• Evaluate solution options based on scientific fit, feasibility, security, scalability, supportability, cost, and risk.
• Partner with architects and engineers to define application, integration, data, cloud, and deployment designs.
• Design and document integrations using APIs, events, data pipelines, and reusable services.
• Coordinate delivery across scientific users, product teams, engineering teams, platform teams, vendors, and implementation partners.
• Serve as a primary technical contact for scientific software vendors, including technical evaluation, integration planning, testing, and deployment.
• Support the integration of data, analytics, predictive models, machine learning, and agent-enabled capabilities into scientific workflows.
• Define testing expectations and coordinate integration, regression, performance, and end-to-end testing.
• Identify technical risks, dependencies, assumptions, and delivery blockers and drive them toward resolution.
• Support application modernization, consolidation, migration, and retirement activities.
• Define operational requirements, support models, monitoring needs, and production-readiness criteria.
• Maintain technical documentation and coordinate applicable security, privacy, architecture, AI, and compliance assessments.
• Mentor less experienced analysts and promote consistent technical analysis and delivery practices.

• Bachelor’s degree with 3+ years of experience in computer science, information technology, engineering, computational science, scientific informatics, or related discipline.
• A master’s degree or PhD in a relevant technical or scientific discipline is advantageous but not required.
• Technical requirements analysis and solution evaluation.
• Scientific workflow and process analysis.
• Application, data, and systems integration.
• REST APIs, event-driven integration, and data pipelines.
• Cloud application and deployment concepts.
• Data analysis and troubleshooting using SQL and scripting.
• Agile product delivery and backlog management.
• Testing and production-readiness planning.
• Vendor and stakeholder management.
• Risk, issue, dependency, and decision management.
• Technical documentation and architecture diagramming.
• Clear communication with scientific, technical, and business audiences.

• Cheminformatics, computational chemistry, scientific informatics, or scientific software.
• Design and implementation of analytics, machine learning, or agentic capabilities within scientific workflows using AI-assisted tools
• Experience working with medicinal chemists, computational chemists, data scientists, or discovery research teams.
• Integration of commercial scientific software with internal applications and data platforms.
• Application modernization, cloud migration, platform consolidation, or system retirement.
• CI/CD, infrastructure as code, automated testing, or cloud deployment practices.
• Pharmaceutical research, biotechnology, or life-sciences experience.
• Cloud architecture or DevOps certification.
  

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