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Specialist Scientific IS Business Analyst

Job in Thousand Oaks, Ventura County, California, 91362, USA
Listing for: BioSpace
Full Time position
Listed on 2026-05-31
Job specializations:
  • IT/Tech
    Data Analyst
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Join Amgen's Mission of Serving Patients

At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission to serve patients living with serious illnesses drives all that we do.

Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas—Oncology, Inflammation, General Medicine, and Rare Disease—we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity‑related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller, happier lives.

Our award‑winning culture is collaborative, innovative, and science‑based. If you have a passion for challenges and the opportunities that lie within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Specialist Scientific IS Business Analyst What You Will Do

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 such as 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 ability 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 data (genomics, proteomics, transcriptomics, epigenomics, etc.). In addition, this role works closely with the 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, ensuring it meets the needs of our Amgen Research community. This role also entails understanding business needs for AI‑enabled solutions and facilitating the building of data connectors to various data sources.

Roles & Responsibilities
  • 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 system 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,…
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