Canada - Burnaby

JOB ID: R-243572 LOCATION: Canada - Burnaby WORK LOCATION TYPE: On Site DATE POSTED: May. 05, 2026 CATEGORY: Scientific SALARY RANGE: 109,254.75 CAD - 147,815.25 CAD

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 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 lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Scientist – Digital Discovery: Biological Data Systems & Machine Learning

What you will do

Let’s do this. Let’s change the world. In this vital role, we are seeking a Scientist, Biological Data Systems & Machine Learning to join the Digital Discovery team. This role sits at the intersection of wet-lab experimental biology, data systems, and machine learning, enabling a closed-loop discovery engine where data generation, structuring, and modeling continuously inform one another.

Scientific Data Architecture & Modeling

• Define and implement data models, schemas, and relationships for biological data
• Ensure robust data lineage, metadata standards, and interoperability across systems
• Establish best practices for ML-ready biological datasets

Legacy Data Mining & Curation for AI/ML

• Identify, access, and harmonize proprietary legacy discovery datasets
• Perform data archaeology to reconstruct experimental context and metadata
• Build high-quality, ML-ready training datasets for model development
• Partner with AI/ML teams on data requirements and dataset design

Experiment–Data–Platform Integration

• Translate experimental workflows into digital systems (e.g., Benchling)
• Define requirements for workflows, entities, and dashboards with engineering teams
• Ensure data is captured in a structured, future-ready manner

Computational Analysis & ML Enablement

• Analyze large-scale biological datasets to generate insights
• Support development of predictive and generative ML models
• Optimize dataset structure and feature engineering

Cross-Functional Integration

• Interface across experimental biology, AI/ML, data engineering, and business teams
• Translate scientific needs into technical requirements and vice versa
• Align workflows with enterprise data ecosystem strategies

Workflow Optimization & Automation

• Identify inefficiencies and design scalable data workflows
• Develop tools and dashboards to improve data accessibility and usability
• Ensure robustness and integrity of datasets and tools
• Identify edge cases and prevent downstream issues

Adoption & Enablement

• Drive adoption of data platforms and best practices
• Serve as a trusted advisor to scientists on data stand