Amgen British Columbia ULC Posted May 5, 2026

Scientist – Digital Discovery: Biological Data Systems & Machine Learning

Burnaby, Canada Full time
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Amgen British Columbia ULC has closed or removed this posting -- see current similar openings below.

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About this opportunity

Career Category

Scientific

Job Description

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 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

OR Master’s degree + 3+ years of relevant experience

OR 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 personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.

Amgen is proud to have been recognized as one of LinkedIn Top 25 Companies in Canada for career growth. Click HERE for more details.

The base salary for this position is $109,255 - $147815.

In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.

Apply now and make a lasting impact with the Amgen team.

careers.amgen.com

As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.

Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

. Salary Range

109,254.75 CAD - 147,815.25 CAD

Job details

Seniority
Not listed
Function
Drug Discovery & Preclinical Research
Therapeutic area
Not listed
Location
Burnaby, Canada
Employment type
Full time

How this role compares

Computed from every other active Drug Discovery & Preclinical Research role in our database, not just this employer's listings.

We currently track 466 comparable Drug Discovery & Preclinical Research roles across 64 biopharma companies.

466Comparable roles tracked
416Currently active
64Companies hiring similar roles
19Countries represented

Salary context

157 of 466 peers report a salary range (USD, annualized)

Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.

This roleSubject $109,255/yr – $147,815/yr
Highest disclosed · Executive Director, Biotherapeutics DMPK · Vertex Pharmaceuticals Inc (US) $268,000/yr – $402,000/yr
Peer group range $0 – $335,000 (median $168,090)

Where these roles are based

Top locations among the 466 comparable roles

United States351
Germany18
India18
United Kingdom12
Switzerland11
Canada10

+ 13 more countries

Seniority mix

373 of 466 peers have a known seniority level

Senior117
Principal82
Intern/Fellow/Postdoc52
Director39
Associate25
Associate Director23
Senior Director15
Executive/VP11
Manager9

Therapeutic area mix

61 of 466 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden

Oncology27
Cardiovascular / CVRM8
Neuroscience8
Immunology7
Vaccines & Infectious Disease3
Respiratory3
Rare Disease3
Ophthalmology1
Gastroenterology1

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Notify me about similar jobs

Get an email when we spot other openings like this one – same job function, comparable seniority, roles you'd actually want to see.

How we calculate "similar"

No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.

Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.

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Function Therapeutic area Seniority Country
Unmatched or unknown dimensions score exactly the same: 0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.