Specialist Scientific IS Business Analyst

Specialist Scientific IS Business Analyst What you will do

Let’s do this. Let’s change the world. In this vital role, you will work closely with Amgen Research partners and Technology peers to ensure that the technology/data needs for drug discovery research are translated into technical requirements for solution implementation. The role leverages scientific domain and business process expertise to detail product requirements as epics and user stories, along with supporting artifacts like business process maps, use cases, and test plans for the software development teams.

This enables the delivery team to estimate, plan, and commit to delivery with high confidence and identify test cases and scenarios to ensure the quality and performance of IT Systems.

You will join a multi-functional team of scientists and software professionals that enables technology and data capabilities to evaluate drug candidates and assess their abilities to affect the biology of drug targets. This team implements software and infrastructure that enables the capture, processing, storage, analysis and reporting of pre-clinical and clinical omics (genomics, proteomics, transcriptomics, epigenomics etc.) data. In addition, this role works closely with In Vivo – biological studies team to support lead optimization studies.

You will collaborate with Product Owners and developers to maintain an efficient and consistent process, ensuring quality deliverables from the team. You will implement and manage scientific software platforms across the research informatics ecosystem, and provide technical support, training, and infrastructure management, and ensure it meets the needs of our Amgen Research community. This role also entails understanding business needs for AI enabled solutions and facilitating building of data connectors to various data sources.

• Function as a Scientific Business Systems Analyst within a Scaled Agile Framework (SAFe) product team.
• Serve as a liaison between global Research Informatics functional areas and global research scientists, prioritizing their needs and expectations.
• Manage a suite of custom internal platforms, commercial off-the-shelf (COTS) software, and systems integrations.
• Translate complex scientific and technological needs into clear, actionable requirements for development teams.
• Stay updated with industry trends, technological advancements, and scientific progress in Omics techniques and advances in imaging techniques (e.g. Radiomics, cell painting, high content cell-based imaging), including data generation, processing, and analysis.
• Develop and maintain a product roadmap that clearly outlines planned features and enhancements, timelines, and milestones.
• Identify and manage risks associated with the systems, including technological risks, scientific validation, and user acceptance.
• Develop documentation, communication plans, and training plans for end users.
• Ensure scientific data operations are scoped into building research-wide Artificial Intelligence and Machine Learning capabilities.
• Ensure operational excellence, cybersecurity, and compliance.
• Collaborate with geographically dispersed teams, including those in North America and other international locations.
• Foster a culture of collaboration, innovation, and continuous improvement.

• Doctorate degree
• Master’s degree and 2 years of Life Sciences, Computer Science, IT, Computational Biology/Bioinformatics or related field
• Bachelor’s degree and 4 years of Life Sciences, Computer Science, IT, Computational Biology/Bioinformatics or related field
• Associate’s degree and 8 years of Life Sciences, Computer Science, IT, Computational Biology/Bioinformatics or related field
• High school diploma / GED and 10 years of Life Sciences, Computer Science, IT, Computational Biology/Bioinformatics or related field

• 4+ years of experience in implementing and supporting biopharma scientific software platforms along with understanding of research in vivo studies and data analytics.

• Expertise in Omics data management and analysis (Genomics, Proteomics, Transcriptomics etc.)…