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Scientific Business Analyst
4 weeks ago
In this vital role, you will be working closely with Amgen Research partners and Technology peers to ensure that the technology and data needs for drug discovery research are translated into technical requirements for solution implementation. You will be a key member of a cross-functional team that implements scientific software platforms for large molecule discovery. The ideal candidate will have deep scientific domain expertise and a passion for ensuring that technology solutions support data integrity and scientific workflows.
Roles & Responsibilities
- Requirements & Analysis: Function as a Scientific Business Systems Analyst within a Scaled Agile Framework (SAFe) product team. You will serve as a liaison between global Research Informatics and research scientists, translating complex scientific needs into clear, actionable requirements, user stories, and supporting artifacts.
- Platform & Technology Management: You will manage a suite of custom internal platforms, Commercial Off-the-Shelf (COTS) software, and system integrations. You will lead the Large Molecule Discovery technology ecosystem and ensure the platform meets requirements for data analysis and data integrity.
- Compliance & Innovation: Ensure operational excellence, cybersecurity, and compliance. You will also ensure that scientific data operations are scoped into building Research-wide Artificial Intelligence/Machine Learning (AI/ML) capabilities.
Technical Skills
- Proven expertise in a scientific domain area and related technology needs.
- Experience with writing user requirements and acceptance criteria in agile project management systems like JIRA.
- Experience in configuration and administration of LIMS/ELN platforms (e.g., Benchling), Discovery software tools (e.g., Geneious, Genedata Screener), and Instrument Automation and Analysis platforms.
- Experience using platforms such as Spotfire, Tableau, Power BI, etc., to build dashboards and reports.
- Understanding of basic data querying using SQL and Databricks.
- Experience with leveraging LLM tools to accelerate software development processes is a plus.
- Experience with cloud (e.g., AWS) and on-premise infrastructure is a plus.
- Experience leading the implementation of scientific software platforms, Electronic Lab Notebook (ELN), or Laboratory Information Management Systems (LIMS) is a plus.
- Knowledge of the antibody discovery design, make, test, and analyze cycle is a plus.
- Experience in AI and machine learning for drug discovery research is a plus.
Qualifications
- A Master's degree with relevant experience, a Bachelor's degree with extensive experience, or a Diploma with a substantial background in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or a related field.
- Experience in implementing and supporting biopharma scientific software platforms is preferred.
