Scientific Business Analyst - Laboratory Information Management Systems (6

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💰 CAD 110,752 - 149,842 / annual
📅 Posted 2026-07-22 · via Himalayas
🏷 Scientific-Business-Analyst,Laboratory-Information-Management-Systems-(LIMS),Life-Sciences-IT,Drug-Discovery-Technology,Scientific-Software-Product-Management,Laboratory-Information-Management-System-Specialist,Senior-Laboratory-Information-Systems-Analyst,Laboratory-Information-Management-Systems-Consulting,Scientific-Business-Analysis
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Job Title: Scientific Business Analyst - Laboratory Information Management Systems (6

Job Location: Ontario, Canada

Job Location Type: Remote

Job Contract Type: Full time
Job Seniority Level:
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. 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 lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
Title: Scientific Business Analyst - LIMS
Term: 6 months
Location: Canada Remote
What you will do

Let’s do this. Let’s change the world. In this vital role you will be working 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 features 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 Laboratory Information Management Systems (LIMS) platforms that enable the capture, analysis, storage, and report of pre-clinical and clinical studies as well as those that manage biological sample banks. You will collaborate with the Product Owner 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.
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 systems integrations

- Lead the technology ecosystem for in vivo study data management and ensure that the platform meets their requirements for data analysis and data integrity

- Translate complex scientific and technological needs into clear, actionable requirements for development teams

- Develop and maintain a product roadmap that clearly outlines the planned features and enhancements, timelines, and milestones

- Identify and manage risks associated with the systems, including technological risks, scientific validation, and user acceptance

- Develop documentations, communication plans and training plans for end users

- Ensure scientific data operations are scoped into building Research-wide Artificial Intelligence/Machine Learning capabilities

- Ensure operational excellence, cybersecurity and compliance.

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