Scientist – Digital Discovery: Biological Data Systems & Machine Learning

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
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 standards and workflows

What We Expect Of You
We are all different, yet we all use our unique contributions to serve patients. The professional we seek is a Scientist with these qualifications.

Basic Qualifications

PhD in Biology, Immunology, Immunoengineering, Biochemistry, Bioengineering or related field

Master’s degree + 3+ years of relevant experience

Bachelor’s degree + 5+ years of relevant experience

Preferred Qualifications

Training in Bioinformatics, or related field

Strong background in wet‑lab biology

Experience with large‑scale biological datasets

Experience with data modeling, curation, and ETL pipelines

Proficiency in Python and/or R

Experience with machine learning approaches

Familiarity with scientific data platforms (e.g., Benchling)

Experience working cross‑functionally across science, data, and engineering teams

What You Can Expect Of Us
As we work to develop treatments that take care of others, we also work to care for your professional and…