The Opportunity:

We are seeking a Senior Manager, Research Informatics to lead the strategy, development, and evolution of research informatics capabilities that accelerate Discovery Research. In this role, you will partner closely with scientific teams, computational scientists, and technology teams to define and deliver scalable digital solutions that transform how scientific data is captured, managed, analyzed, and leveraged across the research organization.

You will lead initiatives to modernize research workflows by driving standardization, automation, expanding the adoption of enterprise platforms over standalone applications, and seamless integration across the research informatics ecosystem. By establishing scalable data frameworks, governance, and best practices, you will enable high-quality, traceable, and reusable scientific data that supports operational excellence, advanced analytics, and AI-enabled discovery. In this role you will be responsible for:

• Develop and execute the research informatics strategy to support scalable, efficient, high-quality workflows across Discovery Research.

• Partner with scientific, computational, and technology teams to align research priorities with informatics capabilities and technology roadmaps.

• Lead the design, governance, and lifecycle management of research data models, templates, workflows, and enterprise platforms, including Genedata Screener and Benchling.

• Automate and optimize data capture, assay analysis, reporting, and system integrations to improve efficiency, reproducibility, and data integrity.

• Establish standards and best practices for data management, metadata, workflow design, system configuration, and application lifecycle management.

• Build partnerships with scientists, computational teams, IT, vendors, and external collaborators to deliver high-impact informatics solutions.

• Prioritize application enhancements, support needs, and operational improvements to maintain strong service levels and user satisfaction.

• Drive user adoption through clear communication, training, change management, and stakeholder engagement.

• Assess emerging technologies, including AI-enabled platforms and advanced analytics, and define implementation strategies that improve scientific productivity.

Required Skills, Experience and Education:

• Bachelor’s degree in a scientific, computational, or related field; advanced degree preferred.

• 7 – 9 years of experience leading research informatics, scientific applications, or laboratory information management initiatives in biotech, pharmaceutical, or research settings.

• Experience with Assay Management platforms such as Genedata Screener, IDBS ActivityBase or Revvity Signals.

• Strong understanding of discovery research workflows, scientific data management, assay informatics, laboratory operations, and research data lifecycle management.

• Experience implementing, optimizing, and governing enterprise scientific platforms and informatics ecosystems.

• Proven ability to translate scientific and business needs into scalable technology solutions and long-term roadmaps.

• Experience leading cross-functional programs with scientists, software engineers, and external vendors.

• Working knowledge of workflow automation, systems integration, data standards, SQL, Python, and modern data integration approaches.

• Excellent communication, leadership, and executive presentation skills, with the ability to influence technical and scientific stakeholders.

• Demonstrated people leadership, coaching, and organizational development experience.

Preferred Skills

• Experience with Genedata Screener, Genedata Expressionist, Benchling, D360, Mosaic, or similar scientific informatics platforms.

• Experience supporting high-throughput screening, assay development, translational research, and discovery research teams.

• Knowledge of APIs, data pipelines, cloud-based research platforms, and enterprise integration architectures.

• Experience establishing research data governance, FAIR data principles, metadata standards, and reusable data frameworks.

• Experience developing informatics capabilities that support machine learning, AI-enabled workflows, or advanced analytics.

• Familiarity with resource planning, roadmap planning, vendor management, software licensing, and budgets. 

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